IRI: http://objects.mainzed.org/type/ont#2DRaster
IRI: http://objects.mainzed.org/type/ont#3DRaster
IRI: https://photogrammetry.altervista.org/items/show/166#F79_Printing_Device
"A SLA (Stereolithography) printer employed for high-resolution prints of intricate designs, which utilizes a laser to cure liquid resin layer by layer."
"An FDM (Fused Deposition Modeling) 3D printer used for creating plastic prototypes, which utilizes a continuous filament of thermoplastic material to construct objects."
IRI: http://objects.mainzed.org/type/ont#4DRaster
IRI: https://photogrammetry.altervista.org/items/show/127#F41_Number_of_Picture
"A photogrammetric acquisition that consists of 150 images captured from various angles around an archaeological site, where F41 would denote the number '150.'" .
IRI: https://photogrammetry.altervista.org/items/show/122#F36_Picture_Carrier
"An SD card storing raw image data from a photogrammetric survey." ;
"An external hard drive containing processed image sets used for 3D reconstruction."
"The server that hosts a cloud storage account that houses the acquired images for future reference and processing." .
IRI: https://photogrammetry.altervista.org/items/show/111#F25_Acquisition_Raw_Data
"LiDAR point cloud data that has not undergone filtering or classification." ;
"Raw laser scan data collected from a laser scanner without any preprocessing." ;
"Unedited images captured by a camera during a photogrammetric survey." ;
IRI: https://photogrammetry.altervista.org/items/show/121#F35_Raw_Data_Carrier
"A USB flash drive with raw laser scan data from an architectural survey." ;
"A cloud storage account holding raw data from a multi-sensor acquisition process." .
"An SD card storing raw image data captured during a photogrammetric acquisition." ;
"An external hard drive containing raw LiDAR data from a topographic survey." ;
IRI: https://photogrammetry.altervista.org/admin/items/show/88#F2_Acquisition
"The photogrammetric survey of a contemporary art sculpture (Ucakar 2022)." ;
"The photogrammetric survey of the walls of Cortona (Lauro 2023)." ;
"The survey of the facade of Bedzin Castle using laser scanning and photogrammetry (Klapa 2017)." ;
IRI: http://objects.mainzed.org/metadata/ont#AcquisitionTechnology
IRI: https://photogrammetry.altervista.org/items/show/287#F108_Calibration_of_the_Instrument
Calibration of a fixed photogrammetry camera system for high-resolution artifact capture.
Pre-acquisition calibration of a laser scanner.
IRI: https://photogrammetry.altervista.org/items/show/286#F106_Acquisition_Location_Type
An indoor environment with low light, such as a museum display room.
An outdoor archaeological site without additional lighting.
IRI: https://photogrammetry.altervista.org/items/show/131#F45__Acquisition_Coordinates
IRI: https://photogrammetry.altervista.org/items/show/129#F43_Survey_Date
"A series of survey dates used for environmental monitoring, indicating repeated data collection at a particular location."
"A timeframe marking different phases of an archaeological excavation, with specific survey dates documenting progress."
"The exact date when a photogrammetric survey was performed at a historic site, such as June 15, 2022."
Example: "The date of a structural survey conducted on a bridge to assess its condition, such as March 1, 2023."
IRI: https://photogrammetry.altervista.org/items/show/130#F44_Acquisition_Description
"A comprehensive account of the photogrammetric survey at an archaeological site, detailing the equipment used, environmental factors, and challenges encountered during the process."
"A narrative summarizing the purpose and methods of the acquisition, such as 'The survey was performed to assess the structural integrity of the building using both photogrammetry and laser scanning techniques.'"
Example: "A description of the laser scanning session, outlining the device's trajectory and highlighting unique features of the scanned object."
IRI: https://photogrammetry.altervista.org/items/show/95#F9_Acquisition_Device
IRI: https://photogrammetry.altervista.org/items/show/288#F109_Marker_and_Calibration_Tools
Markers used in photogrammetry software for real-time calibration.
Prisms applied in total station systems for external coordinate accuracy.
IRI: https://photogrammetry.altervista.org/items/show/106#F20_Acquisition_Device_Type
"Camera: Standard photographic equipment for capturing images." ;
"Handheld Scanners: Portable devices for capturing detailed surface information." .
"Laser Scanner: Device used for capturing 3D data of surfaces through laser measurements." ;
"LiDAR: Technology that measures distances by illuminating a target with laser light and analyzing the reflected light."
"Total Station: An optical/electronic instrument used for surveying and building construction." ;
IRI: https://photogrammetry.altervista.org/items/show/126#F40_Eidotype
"A digital sketch indicating the lighting setup during the survey of a sculptural piece, noting shadows and reflections." ;
"A hand-drawn diagram outlining the positions and angles from which photographs will be taken around an archaeological site." ;
"A visual representation capturing the environmental conditions at the time of acquisition, such as sunlight direction and weather influences." .
"An annotated drawing that describes the planned trajectory of a laser scanner while capturing data from a complex architectural structure." ;
IRI: https://photogrammetry.altervista.org/items/show/104#F18_Dominant_Geometry_Type
"Cylinder: A bottle, defined by its elongated form." ;
"Parallelepiped: A book, reduced to its rectangular prism shape."
"Sphere: A basketball, characterized by its round shape." ;
IRI: https://photogrammetry.altervista.org/items/show/128#F42_Place_Of_Acquisition
" A historic building, like a medieval castle, where the acquisition was performed, serving as the Place of Acquisition." ;
"A landscape feature, such as a valley or a mountain, where the acquisition took place, denoting its significance in geographical studies." ;
"An archaeological site, such as the ruins of an ancient temple, identified as the Place of Acquisition for the photogrammetric survey." ;
"An urban area, like a city square, where multiple structures were surveyed, specified as the Place of Acquisition." .
IRI: https://photogrammetry.altervista.org/items/show/99#F13_Acquisition_Method
"The McGlone Method, which provides a standardized set of steps for capturing imagery in aerial photogrammetry surveys." .
:F13_Acquisition_Method skos:example "The FOPPA protocol for archaeological photogrammetry, which prescribes specific camera settings and trajectories for artifact documentation." ;
IRI: https://photogrammetry.altervista.org/items/show/123#F37_Survey_Operator
"A photogrammetrist operating a drone-mounted camera for aerial image acquisition of an archaeological site." ;
"A surveyor manually collecting geospatial data using a handheld GPS device." ;
"A technician using a laser scanner to capture a 3D model of a historical building." ;
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1Protocol_of_Ontological_Digital_Survey/extensions/versions/1_1/F12_Acquisition_Trajectory#F12_Acquisition_Trajectory
"A modular scanning setup, where a laser scanner is placed at different strategic positions around an architectural site to capture comprehensive point cloud data." .
"A spiral trajectory executed by a camera as it moves around an archaeological artifact for a photogrammetric survey." ;
IRI: https://photogrammetry.altervista.org/items/show/103#F17_Acquisition_Trajectory_Type
"Linear Trajectory: Straightforward movement along a defined line to ensure consistent coverage of the object." ;
"Vertical Scan: Upward or downward movements intended to gather data from different height levels of the subject." .
IRI: https://photogrammetry.altervista.org/items/show/119#F33_Acquisition_Phase
"Laser scanner operating manuals detailing the step-by-step process for capturing modular scans of a structure as Faro Manual (FARO)." ;
"LiDAR survey guidelines that outline specific trajectories and scanning methods for archaeological site documentation." ;
"Photogrammetry acquisition protocols that specify camera settings, shooting angles, and distances for capturing a complete set of images as FOPPA protocol (FOPPA)." ;
"Workflow instructions from photogrammetric or laser scanning handbooks guiding users through the acquisition process as the INCEPTION protocol (Iadanza 2019)." .
IRI: https://photogrammetry.altervista.org/items/show/93#F7_Picture_Set
"Photographs captured for a photogrammetric survey of an archaeological artifact or a historical building." ;
"The 181 photographs that form the photogrammetric survey of the AFMNM005 jaw from the Minamikata excavation (Lauro 2019)." ;
IRI: https://photogrammetry.altervista.org/items/show/92#F6_Acquisition_Raw_Data
IRI: https://photogrammetry.altervista.org/items/show/105#F19_Scale_Type
"Bend (COSCHKR)." ;
"Corner (COSCHKR)." ;
"Joint (COSCHKR)." .
"Medium Object: Ranging from 1 cm to 30 cm (FOPPA)." ;
"Open Architectural Structure: Entire buildings or significant structures (FOPPA)." ;
"Small Object: Equal to or smaller than 1 cm (FOPPA)." ;
IRI: https://photogrammetry.altervista.org/items/show/94#F8_Picture
"A single high-resolution image of an archaeological artifact taken from a specific angle as part of a complete photogrammetric survey." ;
IRI: https://photogrammetry.altervista.org/items/show/116#F30_Acquisition_Software
"An app that controls a handheld 3D scanner during the acquisition phase of a survey." ;
"Dedicated acquisition software used by a laser scanner to record raw point cloud data without performing any processing steps." ;
"The camera control software used during a photogrammetric survey to capture high-resolution images." ;
"The onboard software of a drone camera used for capturing a series of photographs for 3D modeling purposes." .
IRI: https://photogrammetry.altervista.org/items/show/186#F99_AR_Software_Modelling
Unity: A versatile game engine widely used for developing AR applications, providing tools for 3D modeling, animation, and interaction within augmented environments.
Vuforia: An AR development platform that enables developers to create robust augmented reality experiences by recognizing images and objects in real-time, seamlessly integrating virtual content with the physical world.
IRI: http://objects.mainzed.org/agent/ont#Archeologist
IRI: https://photogrammetry.altervista.org/items/show/173#F86_Software_CAD
"AutoCAD, a widely-used CAD software that allows architects and engineers to create precise 2D and 3D drawings and designs, streamlining the design process."
"Revit, a BIM (Building Information Modeling) software that enables users to design buildings and infrastructure with integrated 3D modeling capabilities, enhancing collaboration among project stakeholders."
IRI: http://objects.mainzed.org/metadata/ont#Calibration
IRI: http://objects.mainzed.org/metadata/ont#CalibrationAlgorithm
IRI: http://objects.mainzed.org/type/ont#CalibrationObject
IRI: http://objects.mainzed.org/metadata/ont#CapturingDevice
IRI: http://www.opengis.net/ont/geosparql#Coverage
IRI: http://www.cidoc-crm.org/extensions/crmdig/versions/4.0/D1_Digital_Object#D1_Digital_Object
IRI: http://www.cidoc-crm.org/extensions/crmdig/versions/4.0/D11_Digital_Measurement_Event#D11_Digital_Measurement_Event
IRI: http://www.cidoc-crm.org/extensions/crmdig/versions/4.0/D13_Digital_Information_Carrier#D13_Digital_Information_Carrier
IRI: http://www.cidoc-crm.org/extensions/crmdig/versions/4.0/D14_Software#D14_Software
IRI: http://www.cidoc-crm.org/extensions/crmdig/versions/4.0/D2_Digitization_Process#D2_Digitization_Process
IRI: http://www.cidoc-crm.org/extensions/crmdig/versions/4.0/D7_Digital_Machine_Event#D7_Digital_Machine_Event
IRI: http://www.cidoc-crm.org/extensions/crmdig/versions/4.0/D8_Digital_Device#D8_Digital_Device
IRI: http://www.cidoc-crm.org/extensions/crmdig/versions/4.0/D9_Data_Object#D9_Data_Object
IRI: https://photogrammetry.altervista.org/items/show/183#F96_Database_Architecture
SQL-based databases used for managing 3D models in cultural heritage projects, such as Omeka-s: This architecture supports a structured approach to data management, allowing for the storage of complex data types, including multimedia files, alongside associated metadata.
Wikibase: This platform offers a flexible architecture for storing and retrieving 3D models with rich semantic data, enabling collaborative editing and querying capabilities that enhance accessibility and integration with other datasets.
IRI: https://photogrammetry.altervista.org/items/show/135#F49__Near_Sampling_Points_Range_SFM_Point_Seeds
"Setting a sampling radius of 10 pixels around SfM point seeds to guide the densification process in photogrammetry software (Regard 3D)."
"Specifying the attribute in software that defines the maximum distance within which new points are generated around existing SfM point seeds for terrain modeling (Zephyr 3D)."
IRI: https://photogrammetry.altervista.org/items/show/141#F55_Depth_Noise_Filtering
"In the densified point cloud of AFMNM005, the Depth Noise Filtering includes Adaptive Feature Extraction (AFE), Gradient Field Estimation (GFE), and further Accelerated Gradient Ascent (FAGA) techniques (Lauro 2019)."
IRI: http://www.cidoc-crm.org/cidoc-crm/E1_CRM_Entity#E1_CRM_Entity
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E11_Modification#E11_Modification
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#E12_Production
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E13_Attribute_Assignment#E13_Attribute_Assignment
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E16_Measurement#E16_Measurement
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E18_Physical_Thing#E18_Physical_Thing
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E2_Temporal_Entity#E2_Temporal_Entity
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E22_Human-Made_Object#E22_Human-Made_Object
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E24_Physical_Human-Made_Thing#E24_Physical_Human-Made_Thing
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E28_Conceptual_Object#E28_Conceptual_Object
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E29_Design_or_Procedure#E29_Design_or_Procedure
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E39_Actor#E39_Actor
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E4_Period#E4_Period
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E5_Event#E5_Event
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E52_Time-Span#E52_Time-Span
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E53_Place#E53_Place
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E54_Dimension#E54_Dimension
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E55_Type#E55_Type
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E57_Material#E57_Material
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E59_Primitive_Value#E59_Primitive_Value
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E60_Number#E60_Number
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E62_String#E62_String
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E65_Creation#E65_Creation
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E7_Activity#E7_Activity
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E70_Thing#E70_Thing
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E71_Human-Made_Thing#E71_Human-Made_Thing
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E72_Legal_Object#E72_Legal_Object
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E73_Information_Object#E73_Information_Object
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E77_Persistent_Item#E77_Persistent_Item
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E90_Symbolic_Object#E90_Symbolic_Object
IRI: http://cidoc-crm.org/cidoc-crm/7.1.3/E94_Space_Primitive#E94_Space_Primitive
IRI: http://objects.mainzed.org/agent/ont#Engineer
IRI: http://objects.mainzed.org/metadata/ont#Enviroment
IRI: http://objects.mainzed.org/function/ont#ExportFunction
IRI: https://photogrammetry.altervista.org/items/show/181#F94_3D_Model_for_Database
A 3D representation of an archaeological artifact prepared for storage in a digital archive: This model includes specific metadata and formatting to ensure compatibility with the database schema, allowing for easy access and analysis by researchers.
A model of a historical site optimized for inclusion in a geographic database: This 3D model is designed with spatial data attributes and optimized for geographic information systems (GIS), enabling users to integrate it with other geospatial data for comprehensive analysis.
IRI: https://photogrammetry.altervista.org/items/show/163#F76_3D_Model_for_3D_Print
"A 3D architectural model adjusted for printing, with specific wall thickness and support structures included to ensure stability during the printing process."
"A prototype design modified for 3D printing, ensuring all parts are printable without failure, featuring reinforced joints and proper scaling for accurate representation."
IRI: https://photogrammetry.altervista.org/items/show/171#F84_3D_Model_for_Prospectus
"A modified 3D model of a building used to create architectural plans and sections, facilitating detailed design reviews and construction documentation."
"A terrain model used to generate topographic maps and orthophotos for environmental studies, supporting land use planning and conservation efforts."
IRI: https://photogrammetry.altervista.org/items/show/159#F72_3D_Model_Video_Rendering
"A video showcasing the architectural model of a building, rendered to highlight its design elements for a client presentation, including animated walk-throughs and exterior views."
"An educational video demonstrating the features of a historical artifact through 3D rendering, illustrating its significance and context in an engaging manner."
IRI: https://photogrammetry.altervista.org/items/show/184#F97_AR_3D_Model
A 3D reconstruction of a historical site intended for an AR application: This model allows users to visualize and interact with the historical site in real time, integrating virtual elements with the physical environment to provide contextual information.
A virtual artifact designed to be viewed in a mixed reality setting: This model enhances educational experiences by enabling users to examine and manipulate digital representations of artifacts while simultaneously engaging with their physical surroundings.
IRI: https://photogrammetry.altervista.org/items/show/177#F90_Data_Log_Analysis
"A CSV file detailing measurements and observations from a 3D surface analysis, capturing data points such as depth, texture, and anomalies."
"A log of the parameters used in digital analysis processes, including any findings related to the object being studied, providing context for subsequent evaluations."
IRI: https://photogrammetry.altervista.org/items/show/175#F88_Archaeometric_3D_Model
"A 3D scan of an ancient artifact prepared for materials analysis, enabling researchers to study composition, structural integrity, and historical context."
"A detailed model of a historic building surface analyzed for degradation patterns, assisting in conservation efforts and restoration planning."
IRI: https://photogrammetry.altervista.org/items/show/174#F87_3D_Model_Prospectus
"A set of architectural elevations and floor plans derived from a 3D building model, providing essential information for construction and design validation."
"An orthophoto map created from a topographical model after CAD analysis, serving as a precise representation of land features for environmental studies."
IRI: https://photogrammetry.altervista.org/items/show/168#F81_3D_Model_for_G.I.S.
"A 3D representation of urban infrastructure, adjusted for integration with city planning GIS applications, enabling planners to visualize and analyze spatial relationships and resource allocation."
"A topographical model of a geographical area prepared for environmental analysis within a GIS framework, facilitating assessments of land use, resource management, and ecological impacts."
IRI: https://photogrammetry.altervista.org/items/show/178#F91_Model_for_Interactive
"A 3D reconstruction of an archaeological site created for interactive educational software, allowing users to navigate through the site and access additional information about its history." en
"A digitally enhanced model of a historical building intended for virtual tours, enabling users to explore the interior and exterior while interacting with contextual information about architectural elements."
IRI: https://photogrammetry.altervista.org/items/show/162#F75_Project_Video
"A promotional video that highlights the features of a virtual tour created from a 3D model, incorporating narration and background music for an engaging experience."
"The final video output showcasing a 3D architectural design, ready for client delivery, featuring dynamic angles and detailed animations."
IRI: https://photogrammetry.altervista.org/items/show/91#F5_Exporting
IRI: https://photogrammetry.altervista.org/items/show/185#F98_AR/MR_Project_Implementation
Integrating a virtual object into a mixed reality experience for educational purposes: This step includes aligning the virtual object with real-world surroundings, allowing users to interact with both digital and physical elements seamlessly during an educational activity.
Loading a 3D model into an AR application for mobile devices: This process involves preparing the model for compatibility with mobile AR software, ensuring it can be rendered accurately and interactively in a real-world context.
IRI: https://photogrammetry.altervista.org/items/show/176#F89_Project_Analysis
"Conducting a surface analysis of a 3D archaeological model to identify wear patterns, providing valuable data for understanding historical usage."
"Performing a digital evaluation of a historical artifact to assess its preservation status, helping conservators determine necessary interventions."
IRI: https://photogrammetry.altervista.org/items/show/172#F85_CAD_Analysis
"Analyzing a 3D terrain model to produce accurate orthophotos for cartographic purposes, enhancing geographical representation and analysis."
"Using CAD software to create detailed floor plans and architectural drawings from a 3D model, facilitating design communication and project documentation."
IRI: https://photogrammetry.altervista.org/items/show/182#F95_Database_Project_Implementation
The process of importing a 3D model into a cultural heritage database: This activity includes validating the model's format, ensuring compliance with database schema, and performing quality checks to facilitate accurate representation and retrieval.
Uploading a digital representation of a building to a municipal database for urban planning: This implementation involves configuring the model to align with urban planning standards, tagging it with relevant metadata, and ensuring it integrates seamlessly with existing data layers within the database.
IRI: https://photogrammetry.altervista.org/items/show/160#F73_Editing_Video
"Adding background music and transitions to the video of a 3D model for promotional purposes, enhancing viewer engagement and aesthetic appeal."
"Cutting segments of the 3D rendering video to create a more concise presentation for a seminar, ensuring the key points are highlighted effectively."
IRI: https://photogrammetry.altervista.org/items/show/161#F74_Video_Editing_Software
"Adobe Premiere Pro, used for editing and refining videos of rendered 3D models, offering advanced features like multi-track editing and color correction."
"Final Cut Pro, a software application employed in the editing of architectural visualization videos, known for its intuitive interface and powerful editing tools."
IRI: https://photogrammetry.altervista.org/items/show/158#F71_Final_Use_of_Digital_Twin
"Creating various renditions of a Digital Twin to support different stages of an architectural review process, including detailed models for technical analysis and simplified versions for stakeholder presentations."
"Modifying a Digital Twin for use in a virtual reality simulation for a client presentation, ensuring an immersive experience that highlights key design features."
IRI: https://photogrammetry.altervista.org/items/show/179#F92_Interactive_Project_Implementation
"Incorporating a 3D model into a virtual reality application for educational purposes, allowing students to explore historical sites in an immersive way."
IRI: https://photogrammetry.altervista.org/items/show/164#F77_Printing_Digital_Twin
"The act of 3D printing a prototype based on a digitally designed engineering component, facilitating functional testing and design validation."
"The operation of a 3D printer producing a scaled model of a historical artifact from a digital file, allowing for preservation and study of the original object's features."
IRI: https://photogrammetry.altervista.org/items/show/157#F70_Number_of_Final_Destination
"Count of different cloud storage platforms where copies of a Digital Twin are kept for disaster recovery, including local servers and remote backups."
"The number of backup locations designated for an industrial Digital Twin model, ensuring data redundancy and recovery options in case of system failures."
IRI: https://photogrammetry.altervista.org/items/show/156#F69_Exporting_Description
"A description detailing the export settings used to generate a 3D model in OBJ format from the Digital Twin, specifying resolution and texture mapping options."
"Notes explaining the conversion process of a Digital Twin from a proprietary format to a standard interchange format for wider accessibility, including adjustments made to preserve data integrity."
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1Protocol_of_Ontological_Digital_Survey/extensions/versions/1_1/F47_Densification#F47__Densification
"The densification of a LiDAR point cloud to enhance the resolution and clarity of a 3D terrain model."
Example: "The application of dense matching techniques to generate a more detailed point cloud in architectural surveys."
Example: "The densification of a photogrammetric point cloud by increasing the number of points using stereo-matching algorithms."
IRI: http://objects.mainzed.org/function/ont#FeatureDetectionAlgorithm
IRI: http://objects.mainzed.org/metadata/ont#FusionAlgorithm
IRI: http://objects.mainzed.org/type/ont#GeometricalRepresentation
IRI: http://www.opengis.net/ont/geosparql#Geometry
IRI: https://photogrammetry.altervista.org/items/show/170#F83_GIS_Software
"ArcGIS, a popular GIS software for mapping and spatial analysis, supporting the integration of 3D models to enhance geographical insights and decision-making processes."
"QGIS, an open-source GIS application that allows users to work with 3D representations of spatial data, facilitating collaborative analysis and data sharing."
IRI: https://photogrammetry.altervista.org/items/show/169#F82_Reference_GIS_System
"A conservation GIS employed in environmental management, integrating 3D models of natural landscapes to analyze habitat changes, biodiversity, and land use impacts."
"A municipal GIS used for urban planning and zoning, where the 3D model represents building structures, allowing city planners to visualize spatial relationships and assess the impact of new developments."
IRI: https://photogrammetry.altervista.org/items/show/180#F93_Interactive_Software
Unity: A powerful game engine commonly used for creating interactive applications, allowing developers to incorporate 3D models and develop immersive experiences across various platforms.
Unreal Engine: A comprehensive suite for game development and interactive content creation, providing high-fidelity graphics and tools for integrating complex 3D models into interactive environments.
IRI: https://photogrammetry.altervista.org/items/show/191#F105:_Interrogation_Tools
A curvature analysis tool (F105) was used to evaluate the surface smoothness of a digital 3D model of an ancient sculpture.
A point cloud comparison tool (F105) was employed to assess differences between two scans of a building facade taken months apart to monitor structural changes.
Software-based tools (F105) were applied to a dense point cloud to measure the volume of an archaeological excavation site.
Texture mapping interrogation software (F105) was utilized to assess how accurately textures were applied to a 3D model for virtual exhibition purposes.
IRI: http://www.w3.org/ns/prov#Activity
IRI: http://www.w3.org/ns/prov#Entity
IRI: http://objects.mainzed.org/metadata/ont#MeasurementActivity
IRI: http://objects.mainzed.org/function/ont#MeasurementAlgorithm
IRI: http://objects.mainzed.org/type/ont#Mesh
IRI: http://objects.mainzed.org/metadata/ont#MeshProcessingActivity
IRI: https://photogrammetry.altervista.org/items/show/90#F4_Modelling
"Mesh processing of an excavation sector of the Oglala National Grassland (Douglas 2015)." ;
"The reconstructive modeling of the Temple of Saturn at the Forum in Rome based on the photogrammetric survey of the structure (Koller 2009)." ;
IRI: https://photogrammetry.altervista.org/items/show/142#F56_Mesh_Reconstruction
"Reconstructing the mesh of a building facade from a point cloud acquired through laser scanning in order to create a geometric model for preservation purposes."
Examples: "Generating a 3D mesh from a densified point cloud of an archaeological artifact."
IRI: https://photogrammetry.altervista.org/items/show/151#F64_Modelling_Description
"A description detailing how the texture was adjusted to enhance realism by applying a specific smoothing filter and how additional vertices were added to refine the model's geometry."
"The string 'elimination of the elements of the table and the set and focus on the find' in the context of modeling the 3D model of AF005MNM (Lauro 2019)."
IRI: https://photogrammetry.altervista.org/items/show/144#F58_Modifying_Mesh
"Applying smoothing techniques to a 3D mesh of an archaeological artifact to remove noise and enhance surface quality for digital preservation."
Examples: "Modifying the mesh of a historical monument to correct errors introduced during the scanning process, ensuring a more accurate representation of its geometry."
Examples: "Simplifying the geometry of a complex 3D model for use in a real-time virtual reality environment, reducing the polygon count while preserving essential details."
IRI: https://photogrammetry.altervista.org/items/show/153#F66_Modelling_Determination
"Assessing which elements of a complex architectural model can be simplified or removed to improve rendering performance, such as reducing the number of polygons in non-visible areas."
"Deciding which details in a character model are necessary for animation and which can be omitted to optimize the mesh, focusing on maintaining key features while enhancing computational efficiency."
"Determining the essential structural elements of a historical building model to be preserved while omitting modern additions that detract from its historical integrity.
IRI: https://photogrammetry.altervista.org/items/show/154#F67_Modelling_Elimination
"Executing the deletion of unnecessary polygons from a high-resolution model to reduce file size and processing time, ensuring that the model remains manageable for rendering and analysis."
"Implementing changes to a 3D asset by removing elements deemed redundant or not relevant to the final output, such as extraneous details that do not contribute to the overall visual narrative."
IRI: https://photogrammetry.altervista.org/items/show/152#F65_Modelling_Date
"The F58 Modifyng Mesh of AFMNM005 occurred on 16/03/2019 (Lauro 2019)."
IRI: https://photogrammetry.altervista.org/items/show/109#F23_Reconstruction_Algorithm_Type
"Alpha Shapes: Approaches that create a mesh based on the shape and distribution of points, defining boundaries for the reconstructed surface." ;
"Delaunay Triangulation: Algorithms that maximize the minimum angle of triangles in the mesh, ensuring quality and even distribution of mesh elements." ;
"Incremental Surface Reconstruction: Techniques that progressively build the surface by adding points and connecting them as more data becomes available." .
"Poisson Surface Reconstruction: A method that generates a smooth surface by solving a Poisson equation based on point cloud data." ;
"Triangulation Algorithms: Techniques that connect points in the point cloud to form triangular meshes." ;
IRI: https://photogrammetry.altervista.org/items/show/101#F15_Recontruction_Method
"Applying the Poisson Surface Reconstruction algorithm in Metashape to create a high-fidelity mesh from a dense point cloud."
IRI: https://photogrammetry.altervista.org/items/show/143#F57_Texturing_Mesh
"Applying high-resolution photographic textures to a 3D mesh of a historic building to accurately reflect its original appearance."
"Mapping surface details onto a 3D model of a statue using images captured from various angles to ensure comprehensive coverage and detail."
"Using UV mapping techniques to accurately position and scale textures on a mesh of an archaeological artifact for virtual exhibition."
IRI: https://photogrammetry.altervista.org/items/show/102#F16_Texturing_Method
"Applying the UV Mapping technique in Blender to unwrap a mesh and create texture coordinates for an optimized 3D model." .
"Using Metashape's Blended Mapping algorithm to generate a unified texture from multiple photographs."
IRI: https://photogrammetry.altervista.org/items/show/110#F24__Texturing_Type
Bump Mapping: An algorithm that simulates surface detail by altering the lighting of a model without changing its geometry, giving the illusion of depth." ;
Normal Mapping: Similar to bump mapping, this technique uses a normal map to create detailed surface features by modifying the surface normals of the geometry." ;
Procedural Texturing: Methods that generate textures algorithmically rather than using bitmap images, allowing for dynamic and complex surface appearances." ;
IRI: https://photogrammetry.altervista.org/items/show/97#F11_Modelling_Device
"A high-spec PC equipped with advanced GPUs to handle complex textures and lighting setups for archaeological 3D models." .
"A workstation running 3D modeling software like Blender, Rhino, or Autodesk Maya used for finalizing and optimizing a 3D mesh created from photogrammetry." ;
IRI: https://photogrammetry.altervista.org/items/show/125#F39_Modelling_Operator
"A 3D artist refining a photogrammetric model by adjusting the mesh and geometry to create an accurate virtual reconstruction." ;
"A heritage specialist applying corrections and detailing to a 3D model of a historical building to prepare it for digital archiving." .
"An archaeologist adjusting the 3D model of an ancient artifact to correct deformations or enhance missing sections." ;
"An engineer modifying a 3D laser scan model to meet the specific dimensions needed for a structural analysis project." ;
IRI: http://objects.mainzed.org/function/ont#ModificationFunction
IRI: https://photogrammetry.altervista.org/items/show/118#F32_Modelling_Software
"Programs like Blender, 3ds Max, or Maya, where operators refine models through direct interaction, optimizing them for specific use cases (e.g., rendering, simulation, or 3D printing)." ;
"Rhino or SketchUp used for detailed architectural model editing and enhancement." .
"Software used to modify 3D meshes, adding or removing details, or reshaping the model." ;
IRI: http://objects.mainzed.org/metadata/ont#PointCloud
IRI: http://objects.mainzed.org/type/ont#PointSet
IRI: http://objects.mainzed.org/type/ont#PrintableMesh
IRI: https://photogrammetry.altervista.org/items/show/165#F78_Material_for_3D_Printing
"ABS (Acrylonitrile Butadiene Styrene) chosen for its durability in engineering applications, making it suitable for creating functional parts that require impact resistance."
"PLA (Polylactic Acid) used for printing biodegradable models, offering an eco-friendly alternative for producing prototypes and consumer products."
IRI: https://photogrammetry.altervista.org/items/show/167#F80_Printed_Digital_Twin
"A 3D printed model of a historical structure used for educational purposes in a museum, allowing visitors to explore architectural details in a hands-on manner."
"A prototype of a product that has been physically produced from its digital twin for testing and evaluation, enabling designers to assess form, fit, and function before mass production."
IRI: https://photogrammetry.altervista.org/items/show/138#F52_Dense_Point_Cloud_Measurement
IRI: https://photogrammetry.altervista.org/items/show/139#F53_Dense_Point_Cloud_Number_of_Point
"A dense point cloud of a scanned monument containing 15 million points."
IRI: https://photogrammetry.altervista.org/items/show/113#F27_Densified_Point_Cloud
"A point cloud obtained after applying algorithms that increase the density of points to capture finer details of an archaeological site." ;
"A processed point cloud used for advanced analysis and 3D reconstruction, characterized by a higher density of points compared to the initial output." ;
"Densified point data generated from a laser scanner, where additional points are added to improve spatial resolution." ;
"Enhanced point cloud data created through interpolation techniques to fill gaps in the original point set." .
Definition of the class F27 Densified Point Cloud as a subclass of D9 Data Object
IRI: https://photogrammetry.altervista.org/items/show/190#F104:_Registration_(Fusion_of_Multiple_Point_Clouds_or_3D_Models)
Automated registration (F104) was applied to fuse point clouds captured from aerial and ground-based photogrammetry, creating a comprehensive 3D model for analysis.
During the photogrammetric survey of a large site, registration (F104) was used to merge multiple 3D models captured from different sections, resulting in a unified representation of the site.
The registration (F104) of two overlapping point clouds from different vantage points was performed to generate a complete 3D model of an ancient temple.
IRI: https://photogrammetry.altervista.org/items/show/114#F28_3D_Mesh
"A 3D model of a building produced from point cloud data that highlights the architectural elements without color or texture as the Buddha of Bamiyan (Gruen 2004)." .
"A geometric representation of an archaeological artifact created from a densified point cloud, showing its contours and surface features as the AF005MNM (Lauro 2019)." ;
IRI: https://photogrammetry.altervista.org/items/show/147#F60_Smoothing_Filter
"A Gaussian smoothing filter applied to a 3D mesh to create a more fluid surface by averaging the vertices of the mesh."
"A Laplacian smoothing filter used during the creation of a 3D mesh to reduce sharp edges and create a smoother transition between different surface areas."
IRI: https://photogrammetry.altervista.org/items/show/112#F26_Point_Cloud
"A collection of 3D points representing the surface of an archaeological artifact as captured from raw data." ;
"Initial point cloud data generated from a laser scanner before any further processing steps." ;
"Sparse point data that outlines the basic shape and features of an object without refinement." ;
"The set of points collected from an acquisition with a total station placed in relation in a coordinate grid." .
IRI: https://photogrammetry.altervista.org/items/show/136#F50_Point_Cloud_Measurement
"Assessing the density of points within a 1 cm² area of a point cloud representing an archaeological artifact."
"Measuring the completeness of a point cloud in terms of coverage percentage over a given surface."
"Measuring the number of points in a point cloud generated by a terrestrial laser scanner."
"Recording the spatial accuracy of a point cloud based on the standard deviation of point positions."
IRI: https://photogrammetry.altervista.org/items/show/137#F51_Point_Cloud_Number_of_Point
"A laser-scanned point cloud consisting of 1.2 million points."
"A point cloud generated from a photogrammetry survey containing 500,000 points."
"A point cloud obtained from aerial photogrammetry with 750,000 points."
IRI: https://photogrammetry.altervista.org/items/show/115#F29_Textured_3D_Mesh
"A detailed representation of a historical artifact, showing surface textures and markings based on high-resolution photographs." ;
"A fully textured 3D model of an archaeological site that reflects the original colors and patterns of the materials used as for the excavation in Gobelklitepe (Polat 2020)." ;
"An interactive exhibition display featuring a textured model that enhances the viewer's understanding of the object's form and details as the objects displayed in project BeaVIR (Murtas 2023)." .
IRI: https://photogrammetry.altervista.org/items/show/148#F61_Color_Balance/Multiband_Texture
"A color balance adjustment applied to the texture of a 3D architectural model to ensure that the colors accurately reflect the materials used in the real-world structure."
"A multiband texture that combines data from different spectral bands (such as RGB and infrared) to create a detailed and informative texture for a 3D model of a vegetation area."
IRI: https://photogrammetry.altervista.org/items/show/150#F63_Number_of_Texture
"A Texture Set of 3D Mesh consisting of 3 textures, including a diffuse texture for the base color, a normal texture for surface detail, and a specular texture for shininess."
"A Texture Set of 3D Mesh that incorporates 5 different textures, each applied to various components of a complex architectural model, such as walls, roofs, windows, and doors."
IRI: https://photogrammetry.altervista.org/items/show/149#F62_Texture_Set_of_3D_Mesh
"A collection of multiple textures applied to different parts of a 3D character model, including skin texture, clothing texture, and accessory texture, to achieve a rich and detailed visual representation."
"A texture set consisting of a diffuse map, a normal map, and a specular map used to create a realistic surface appearance for a 3D model of a stone wall."
IRI: https://photogrammetry.altervista.org/items/show/89#F3_Processing
"The processing of Bayman's photographs of the Buddha (A. Gruen 2004)." ;
"The processing of photographs of the photogrammetric survey of a wild boar jaw from the Minamikata site (Lauro 2019)." ;
IRI: http://objects.mainzed.org/function/ont#ProcessingFunction
IRI: https://photogrammetry.altervista.org/items/show/133#F47:_Densification
Applying densification algorithms in UAV (drone) imagery processing to achieve high-definition surface models.
The densification of a LiDAR point cloud to increase the resolution and clarity of a 3D terrain model.
The densification of a photogrammetric point cloud by increasing the number of points through stereo-matching algorithms.
The use of dense matching techniques to generate a more detailed point cloud in architectural surveys.
IRI: https://photogrammetry.altervista.org/items/show/108#F22_Densification_Algorithm_Type
"Depth Map Fusion: Algorithms that combine depth maps from multiple scans to create a denser point cloud." ;
"Multi-View Densification: Methods that utilize multiple images to enhance point cloud density through additional data capture." ;
"Point Cloud Densification: Algorithms that interpolate additional points between existing points to increase density." ;
"Regularization Techniques: Approaches that improve point distribution and reduce noise in the densified point cloud." .
IRI: https://photogrammetry.altervista.org/items/show/134#F48_Densification_Method
"A specialized LiDAR data densification method used to capture finer features of a landscape."
"The Semi-Global Matching (SGM) algorithm applied during densification to create detailed terrain models in UAV mapping."
"The algorithm used for dense matching in software to enhance point density in architectural heritage documentation."
"The multi-view stereo (MVS) algorithm for densifying a sparse photogrammetric point cloud."
IRI: https://photogrammetry.altervista.org/items/show/132#F46:_Matching
"Matching points between historical photographs and contemporary images for comparative analysis in archaeological studies."
"The automatic feature matching between pairs of photographs in a photogrammetric workflow to generate an initial sparse point cloud."
"The manual identification of common points between overlapping images when automatic matching algorithms fail."
"The matching of points from multiple LiDAR scans to unify different scan positions into a coherent 3D point cloud."
IRI: https://photogrammetry.altervista.org/items/show/189#F103:_Calibration_(Camera_Calibration)
A camera calibration (F103) was performed prior to a photogrammetric survey to correct for optical lens distortion and improve the accuracy of the generated 3D model.
During image acquisition for an archaeological project, camera calibration (F103) enabled the collection of optimized data for subsequent 3D model creation.
The calibration (F103) was applied to correctly align multiple images in photogrammetry software, ensuring an accurate reconstruction of the 3D scene.
IRI: https://photogrammetry.altervista.org/items/show/107#F21_Matching_Algorithm_Type
"Depth Map Algorithms: Methods that generate depth information from laser scanner data." .
"Feature Matching: Algorithms that identify and match distinctive features in overlapping images." ;
"Stereo Matching: Techniques that derive depth information from two or more images taken from different viewpoints." ;
"Structure from Motion (SfM): Algorithms that reconstruct 3D structures from a series of 2D images."
IRI: https://photogrammetry.altervista.org/items/show/100#F14_Matching_Method
"The FOPPA protocol for archaeological photogrammetry, which prescribes specific camera settings and trajectories for artifact documentation." ;
"The McGlone Method, which provides a standardized set of steps for capturing imagery in aerial photogrammetry surveys." .
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1Protocol_of_Ontological_Digital_Survey/extensions/versions/1_1/F54_Point_Cloud_Vertex_Quality#F54_Point_Cloud_Vertex_Quality
IRI: https://photogrammetry.altervista.org/items/show/96#F10_Processing_Device
A high-performance computer equipped with photogrammetry software (e.g., Agisoft Metashape or Zephyr) used to process survey images into 3D models.
A laser scanner that both collects and processes point cloud data directly within its onboard system.
IRI: https://photogrammetry.altervista.org/items/show/124#F38_Processing_Operator
"A 3D specialist refining raw data from a LiDAR survey into a structured, usable format." ;
"A technician using photogrammetric software to process raw images and generate a point cloud." ;
"An archaeologist processing drone-acquired images to produce orthophotos and digital terrain models." .
"An engineer running processing software on laser scan data to create a densified point cloud." ;
IRI: https://photogrammetry.altervista.org/items/show/120#F34_Processing_Phase
"Guidelines for densifying a point cloud, using specific software configurations (Douglas 2017)." .
"Instructions for generating initial point clouds from photogrammetric images, detailing matching algorithm parameters (FOPPA)." ;
"Protocols for processing laser scan data, including steps for point cloud registration and noise filtering (Iadanza 2019)." ;
IRI: https://photogrammetry.altervista.org/items/show/117#F31_Processing_Software
"A 3D laser scanner’s companion software that converts raw scan data into a structured point cloud and performs densification." ;
"LiDAR processing software that translates raw light detection and ranging data into a detailed and accurate point cloud." ;
"Software that processes photogrammetric images into an initial sparse point cloud and subsequently applies densification algorithms." ;
IRI: http://objects.mainzed.org/function/ont#RemoveFunction
IRI: http://www.cidoc-crm.org/extensions/crmsci/versions/2.0/S10_Material_Substantial#S10_Material_Substantial
IRI: http://www.cidoc-crm.org/extensions/crmsci/versions/2.0/S15_Observable_Entity#S15_Observable_Entity
IRI: http://www.cidoc-crm.org/extensions/crmsci/versions/2.0/S21_Measurement#S21_Measurement
IRI: http://www.cidoc-crm.org/extensions/crmsci/versions/2.0/S4_Observation#S4_Observation
IRI: http://objects.mainzed.org/type/ont#ShapeRepresentation
IRI: https://photogrammetry.altervista.org/admin/items/show/87#F1_Survey_Object
"A castle surveyed with photogrammetric technique (Artopoulos 2015)" ;
"A fresco in a medieval chapel (D. Abate 2016)" ;
"A wild boar jaw AFMNM005 detected with photogrammetric technique at the laboratory of the archaeological museum of Okayama (Japan) coming from the Minamikata excavation in the context of the BeArchaeo project (Lauro, 2019)" ;
IRI: https://photogrammetry.altervista.org/items/show/187#F101_Survey_Phase
The Survey Phase involved an initial site walk-through and preparation, followed by the actual data acquisition using a terrestrial laser scanner.
IRI: http://objects.mainzed.org/type/ont#Tool
IRI: https://photogrammetry.altervista.org/items/show/188#F102:_3D_Digital_Asset
A 3D Digital Asset was created as a Textured 3D Mesh (F29) of a historical monument, used for digital documentation and preservation.
A 3D Model for GIS (F81) was developed to integrate geographical and cultural heritage data into a spatial analysis platform.
The 3D Digital Twin (F100) of an industrial component was generated for predictive maintenance and simulations.
IRI: https://photogrammetry.altervista.org/items/show/145#F100_3D_Digital_Twin
"The digital twin of the boar jaw preserved at the Okayama archaeological museum and signed as AF005MNM (Lauro 2019)."
"The digital twin of the excavation section of the Gobekli Tepe site (Polat 2020)."
"The digital twin of the no longer existing Bamiyan Buddhas (Gruen 2004)."
IRI: https://photogrammetry.altervista.org/items/show/155#F68_Digital_Twin_Physical_Carrier
"An external hard drive containing the files of a Digital Twin for an architectural project, ensuring that all relevant data is securely stored and easily retrievable for future reference."
"The server that hosts the cloud storage service that stores backups of a Digital Twin for an industrial application, providing redundancy and access from multiple locations."
IRI: https://photogrammetry.altervista.org/items/show/146#F59_Digital_Scale
"A digital scale of 1:1 for a final 3D model of a sculpture, indicating that the model is an exact replica of the original size."
"A digital scale of 1:50 for an architectural model, showing that the digital representation is 50 times smaller than the actual building."
IRI: http://objects.mainzed.org/metadata/ont#VertexMeasures
IRI: https://photogrammetry.altervista.org/items/show/280#Y79:_consists_of_printing_material
The Printed Digital Twin consists of Material for 3D Raw, such as PLA or resin.
IRI: https://photogrammetry.altervista.org/items/show/229#Y38_was_measured_in__number_of_points
A F27 Dense Point Cloud was measured in an F52 Dense Point Cloud Measurement, which recorded the number of points after densification.
IRI: https://photogrammetry.altervista.org/items/show/262#Y72_had_final_use_output
The F71 Final Use of the 3D Model has produced F72 3D Model Video Rendering and F76 3D Model for 3D Print as output formats for different applications.
IRI: https://photogrammetry.altervista.org/items/show/260#Y70_Final_Use_of_3D_Model_consist_of
The F5 Exporting phase defines that the F71 Final Use of the 3D Model will be for 3D printing.
IRI: https://photogrammetry.altervista.org/items/show/213#Y22_had_acquisition_input
A processing phase F3 Processing has as input F25 Acquisition Raw Data, which was generated by a laser scan.
IRI: https://photogrammetry.altervista.org/items/show/274#Y85:_had_archaeometric_input
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IRI: https://photogrammetry.altervista.org/items/show/273#Y86:_had_data_log_analysis_output
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IRI: https://photogrammetry.altervista.org/items/show/272#Y87:_had_3D_model_interactive_as_input
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IRI: https://photogrammetry.altervista.org/items/show/270#Y89:_had_3D_model_for_database_as_input
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IRI: https://photogrammetry.altervista.org/items/show/283#Y82:_had_model_prospectuses_for_CAD_as_input
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IRI: https://photogrammetry.altervista.org/items/show/193#Y2:__had_pictures_input
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IRI: https://photogrammetry.altervista.org/items/show/285#Y84:_had_prospectus_output
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IRI: https://photogrammetry.altervista.org/items/show/263#Y73:_had_rendering_as_input
The Editing Video process had a Rendering as input, handled by Video Editing Software such as Adobe Premiere.
IRI: https://photogrammetry.altervista.org/items/show/268#Y91:_had_3D_model_for_AR_as_input
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IRI: https://photogrammetry.altervista.org/items/show/276#Y75:_had_Video_output
The Editing Video process produced a Project Video as output, which can be used for presentation or further rendering.
IRI: https://photogrammetry.altervista.org/items/show/199#Y8_happened_on_acquisition_device
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IRI: https://photogrammetry.altervista.org/items/show/241#Y50_happened_on_modelling_device
A F58 Modifying Mesh process happened on an F11 Modelling Device, such as a high-end 3D modelling workstation.
IRI: https://photogrammetry.altervista.org/items/show/215#Y24_happened_on_processing_device
A processing phase F3 Processing happens on a F10 Processing Device, such as a high-performance server.
IRI: https://photogrammetry.altervista.org/items/show/200#Y9_has_acquisition_device_type
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IRI: https://photogrammetry.altervista.org/items/show/208#Y17:_has_acquisition_operator
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IRI: https://photogrammetry.altervista.org/items/show/248#Y57_has_color_balance/multiband
A F62 Texture Set of 3D Mesh has a F61 Color Balance/Multiband Texture applied to achieve a natural and balanced appearance.
IRI: https://photogrammetry.altervista.org/items/show/212#Y21:_has_coordinates_of_acquisition
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IRI: https://photogrammetry.altervista.org/items/show/223#Y31_has_created_densified_point_cloud
The relation why a F47 Densification phase creates a F27 Densified Point Cloud with a higher density than the original input.
IRI: https://photogrammetry.altervista.org/items/show/240#Y49_has_created_Digital_Twin
A F58 Modifying Mesh process has created a F100 Digital Twin, accurately representing the physical object.
IRI: https://photogrammetry.altervista.org/items/show/221#Y30_has_created_point_cloud
The relation that from F46 Matching process creates a F26 Point Cloud as its final output.
IRI: https://photogrammetry.altervista.org/items/show/201#Y10_has_created_raw_data
The relation between the point cloud data generated and the laser scanning session.
The relation between the raw images captured and the photogrammetric survey of a building façade.
IRI: https://photogrammetry.altervista.org/items/show/245#Y54_has_created_textured_3d_mesh
A F57 Texturing Mesh process has created a F29 Textured Mesh, which includes both geometry and applied textures.
IRI: https://photogrammetry.altervista.org/items/show/237#Y46_has_created_3D_Mesh
A F56 Mesh Reconstruction process has created a F28 3D Mesh representing the geometry of the scanned object.
IRI: https://photogrammetry.altervista.org/items/show/210#Y19:_has_date_of_acquisition
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IRI: https://photogrammetry.altervista.org/items/show/254#Y63_has_date_of_modelling
A F58 Modifying Mesh process has a F65 Modelling Date, such as "August 12, 2023," marking when the model was altered.
IRI: https://photogrammetry.altervista.org/items/show/227#Y36_has_Depth_Noise_Filtering
A F27 Dense Point Cloud undergoes F55 Depth Noise Filtering to remove noise from the depth data.
IRI: https://photogrammetry.altervista.org/items/show/246#Y55_has_digital_scale
A F100 Digital Twin has a F59 Digital Scale of 1:50, representing the scale used to model the digital twin.
IRI: https://photogrammetry.altervista.org/items/show/195#Y4_has_dominant_geometry_type
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IRI: https://photogrammetry.altervista.org/items/show/220#Y29_has_matching_input
A F47 Densification phase uses an input F26 Point Cloud, obtained from a preliminary laser scan.
IRI: https://photogrammetry.altervista.org/items/show/198#Y7_has_method_of_acquisition
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IRI: https://photogrammetry.altervista.org/items/show/218#Y27_has_method_of_densification
A F47 Densification phase uses a F48 Densification Method, such as Multi-View Stereo (MVS) to increase point density.
IRI: https://photogrammetry.altervista.org/items/show/222#Y32_has_method_of_matching
The relation between a F46 Matching process and the F14 Matching Method, such as feature-based matching from images.
IRI: https://photogrammetry.altervista.org/items/show/238#Y47_has_method_of_reconstruction
A F56 Mesh Reconstruction process uses a F15 Reconstruction Method, such as a surface reconstruction technique.
IRI: https://photogrammetry.altervista.org/items/show/239#Y48_has_method_of_texturing
A F57 Texturing Mesh process uses a F16 Texturing Method, such as UV Mapping for applying textures to a 3D mesh.
IRI: https://photogrammetry.altervista.org/admin/items/show/253#Y62_has_modelling_operator
A F4 Modelling process was carried out by a F39 Modelling Operator, such as a skilled 3D artist or modeller.
IRI: https://photogrammetry.altervista.org/items/show/209#Y18:_has_place_of_acquisition
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IRI: https://photogrammetry.altervista.org/items/show/278#Y77:_has_printed_physical_digital_twin
The Printing Digital Twin process produced a Printed Digital Twin, representing the physical counterpart of the digital model.
IRI: https://photogrammetry.altervista.org/items/show/231#Y40:_has_processing_operator
A F3 Processing phase is carried out by a F38 Processing Operator, such as an engineer overseeing the data processing.
IRI: https://photogrammetry.altervista.org/items/show/230#Y39_has_Sampling_Points_Range
The relation that connect a F27 Dense Point Cloud that has a F49 Near Sample Point Range, describing the spread of sampling points in the dataset.
IRI: https://photogrammetry.altervista.org/items/show/196#Y5_has_scale_type
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IRI: https://photogrammetry.altervista.org/items/show/247#Y56_has_smoothing_filter
A F28 3D Mesh has been assigned a F60 Smoothing Filter to soften rough areas in the model.
IRI: https://photogrammetry.altervista.org/items/show/258#Y68_has_Textured_3D_Model_as_input
During the F5 Exporting process, a F29 Textured 3D Model was used as input for generating a final 3D product.
IRI: https://photogrammetry.altervista.org/items/show/259#Y69_has_Digital_Twin_as_output
A F5 Exporting phase has produced a F100 Digital Twin, representing the final exported digital copy of the model.
IRI: https://photogrammetry.altervista.org/items/show/194#Y3:_has_Type_Of_Acquisition
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IRI: https://photogrammetry.altervista.org/items/show/219#Y28__has_type_of_densification
A F48 Densification Method uses a F22 Densification Algorithm Type, such as a dense feature matching algorithm.
IRI: https://photogrammetry.altervista.org/items/show/214#Y23_has_type_of_matching
The F14 Matching Method uses a F21 Matching Algorithm Type, such as a keypoint-based algorithm.
IRI: https://photogrammetry.altervista.org/items/show/235#Y44_has_type_of_reconstruction
A F15 Reconstruction Method uses a F23 Reconstruction Algorithm Type, such as a volumetric method for mesh creation.
IRI: https://photogrammetry.altervista.org/items/show/234#Y43_has_type_of_texturing
A F16 Texturing Method has a F24 Texturing Type, such as UV Mapping applied to a 3D model.
IRI: https://photogrammetry.altervista.org/items/show/226#Y35_has_vertex_quality_assignment
A F26 Point Cloud has an assigned F54 Point Cloud Quality Assignment, indicating the quality of the vertices based on precision.
IRI: https://photogrammetry.altervista.org/items/show/192#Y1:_is_acquired_object_of
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IRI: https://photogrammetry.altervista.org/items/show/206#Y15:_is_composed_of_picture
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IRI: https://photogrammetry.altervista.org/items/show/281#Y80:_is_in_GIS
The 3D Model for GIS is included in a Reference GIS System like ArcGIS for geospatial analysis.
IRI: https://photogrammetry.altervista.org/items/show/250#Y59__is_texture_set_of
A F62 Texture Set of 3D Mesh is part of a F29 Textured Mesh, providing the texture details for the mesh.
IRI: https://photogrammetry.altervista.org/admin/items/show/256#Y66_is_Digital_Twin_physical_carrier
A F68 Model Physical Carrier (a hard drive) stores a F100 Digital Twin of a heritage monument.
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#L1_digitized_(was_digitized_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#L10_had_input_(was_input_of)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#L11_had_output_(was_output_of)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#L12_happened_on_device_(was_device_for)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#L17_measured_thing_of_type_(was_type_of_thing_measured_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#L19_stores_(is_stored_on)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#L23_used_software_or_firmware_(was_software_or_firmware_used_by)
IRI: https://photogrammetry.altervista.org/items/show/242#Y51_Modelling_is_composed_of
A F4 Modelling process consists of F56 Mesh Reconstruction, F57 Texturing Mesh, and F58 Modifying Mesh, to complete the full 3D model.
IRI: https://photogrammetry.altervista.org/items/show/255#Y65_Modelling_is_influenced_by
A F58 Modifying Mesh process is influenced by a F66 Modelling Determination, such as a specific requirement to improve edge flow or reduce polygon count in the model.
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#O24_measured_(was_measured_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#O8_observed_(was_observed_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P1_is_identified_by_(identifies)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P10_falls_within_(contains)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P106_is_composed_of_(forms_part_of)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P108_has_produced_(was_produced_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P11_had_participant_(participated_in)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P12_occurred_in_the_presence_of_(was_present_at)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P125_used_object_of_type_(was_type_of_object_used_in)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P128_carries_(is_carried_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P130_shows_features_of_(features_are_also_found_on)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P132_spatiotemporally_overlaps_with
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P134_continued_(was_continued_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P14_carried_out_by_(performed)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P140_assigned_attribute_to_(was_attributed_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P141_assigned_(was_assigned_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P15_was_influenced_by_(influenced)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P16_used_specific_object_(was_used_for)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P161_has_spatial_projection_(is_spatial_projection_of)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P169_defines_spacetime_volume_(spacetime_volume_is_defined_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P17_was_motivated_by_(motivated)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P2__has_type_(is_type_of)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P31_has_modified_(was_modified_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P33_used_specific_technique_(was_used_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P39_measured_(was_measured_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P4_has_time-span_(is_time-span_of)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P43_has_dimension_(is_dimension_of)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P9_consists_of_(forms_part_of)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P92_brought_into_existence_(was_brought_into_existence_by)
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P94_has_created_(was_created_by)
IRI: https://photogrammetry.altervista.org/items/show/225#Y34_was_measured_in__number_of_points
A F26 Point Cloud was measured in an F50 Point Cloud Measurement, which recorded the total number of points.
IRI: https://photogrammetry.altervista.org/items/show/236#Y45_point_cloud_input
A F56 Mesh Reconstruction process takes in a F27 Densified Point Cloud as input for generating a 3D mesh.
IRI: https://photogrammetry.altervista.org/items/show/277#Y76:_printing_based_on
The Printing Digital Twin process is based on the 3D Model for 3D Print that was developed during the modelling phase.
IRI: https://photogrammetry.altervista.org/items/show/216#Y25_Processing_is_composed_of
A F3 Processing phase is composed of a F46 Matching phase followed by a F47 Densification phase, the property connect this relation.
IRI: https://photogrammetry.altervista.org/items/show/205#Y14:_stores_acquisition_Picture
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IRI: https://photogrammetry.altervista.org/items/show/244#Y53_had_Textured__3d_mesh_input
A F29 Textured Mesh serves as the input for an F58 Modifying Mesh process, where the textured mesh will undergo further refinement.
IRI: https://photogrammetry.altervista.org/items/show/243#Y52_had_3d_mesh_input
A F28 3D Mesh is the input for a F57 Texturing Mesh process, where textures will be applied to the mesh.
IRI: https://photogrammetry.altervista.org/items/show/204#Y13:_used_Acquisition_Instruction
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IRI: https://photogrammetry.altervista.org/items/show/202#Y11_used_acquisition_software
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IRI: https://photogrammetry.altervista.org/items/show/267#Y92:_used_AR/MR_software
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IRI: https://photogrammetry.altervista.org/items/show/284#Y83:_used_CAD_software
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IRI: https://photogrammetry.altervista.org/items/show/269#Y90:_used_database_software/architecture
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IRI: https://photogrammetry.altervista.org/items/show/282#Y81:_used_GIS_software
The Reference GIS System used GIS Software such as QGIS to integrate the 3D model with geographic data.
IRI: https://photogrammetry.altervista.org/items/show/271#Y88:_used_interactive_software
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IRI: https://photogrammetry.altervista.org/items/show/252#Y61_used_modelling_software
A F58 Modifying 3D Mesh process used F32 Modelling Software, such as Blender or Autodesk Maya, to alter the 3D model.
IRI: https://photogrammetry.altervista.org/items/show/232#Y41_used_Processing_Instruction
A F3 Processing phase uses specific F34 Processing Phase Instructions, detailing how to process a point cloud such as the BeAPG Protocol in the processing of AFMNM005 (Lauro 2019).
IRI: https://photogrammetry.altervista.org/items/show/217#Y26__used_processing_software
A F3 Processing phase uses F31 Processing Software, such as CloudCompare for handling point cloud data.
IRI: https://photogrammetry.altervista.org/items/show/279#Y78:_used_specific_printing_machine
The Printing Digital Twin process used a Printing Device like an SLS 3D printer
IRI: https://photogrammetry.altervista.org/items/show/197#Y6_used_trajectory
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IRI: https://photogrammetry.altervista.org/items/show/275#Y74:_use_video_editing_software
The Editing Video phase used Video Editing Software like Final Cut Pro to edit a 3D rendering video
IRI: https://photogrammetry.altervista.org/items/show/257#Y67_was_continued_by_Exporting_phase
A F4 Modelling process was continued by a F5 Exporting phase, where the model was exported in a standard format, like OBJ or STL.
IRI: https://photogrammetry.altervista.org/items/show/233#Y42_was_continued_by_Modelling_phase
A F3 Processing phase was continued by an F4 Modelling phase, where a 3D model was generated from the processed data.
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Y12_was_continued_by_Processing_Phase
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IRI: https://photogrammetry.altervista.org/items/show/266#Y93:_was_continued_by_subsequent_phase
A Survey Phase focused on preliminary data gathering was continued by a subsequent Survey Phase dedicated to higher-resolution data acquisition.
IRI: https://photogrammetry.altervista.org/items/show/264#Y95:_was_measured_in_number_of_points
A F26 Point Cloud was measured in F50 Point Cloud Measurement, which recorded 600,000 points in a typical scan.
A F27 Dense Point Cloud was measured in F52 Dense Point Cloud Measurement, which recorded 15,000,000 points in a high-resolution scan.
IRI: https://photogrammetry.altervista.org/items/show/228#Y37:_has_observed_number_of_points_(for_dense_point_clouds)
A F52 Dense Point Cloud Measurement records an observed number of F53 Dense Point Cloud Number of Points, such as 10,000,000 points in a densified scan.
IRI: https://photogrammetry.altervista.org/items/show/211#Y20:_has_acquisition_description
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IRI: https://photogrammetry.altervista.org/items/show/251#Y60:_has_modelling_description
A F4 Modelling process has a F64 Modelling Description, such as an explanation of the procedural steps used to create the 3D model.
IRI: https://photogrammetry.altervista.org/items/show/207#Y16:_has_number_of_picture
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IRI: https://photogrammetry.altervista.org/items/show/249#Y58:_has_number_of_texture
A F62 Texture Set of 3D Mesh has F63 Number of Texture, indicating the number of individual texture files used in the set.
IRI: https://photogrammetry.altervista.org/items/show/265#Y94:_has_observed_number_of_points
A F50 Point Cloud Measurement records an observed number of F51 Point Cloud Number of Points, such as 500,000 points in a basic scan.
A F52 Dense Point Cloud Measurement records an observed number of F53 Dense Point Cloud Number of Points, such as 12,000,000 points in a densified scan.
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P3_has_note
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#P40_observed_dimension_(was_observed_in)
IRI: https://photogrammetry.altervista.org/items/show/224#Y33:_has_observed_number_of_points
A F50 Point Cloud Measurement records an observed number of F51 Point Cloud Number of Points, such as 1,000,000 points in a scan.
IRI: https://photogrammetry.altervista.org/items/show/261#Y71:_has_number_of_final_destination
The F71 Final Use of the 3D Model has F70 Number of Final Destination, such as three different output formats: video rendering, printing, and research.
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Y19:_has_date_of_acquisition
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Y21:_has_coordinates_of_acquisition
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Y63_has_date_of_modelling
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Y95:_was_measured_in_number_of_points
IRI: http://purl.org/dc/elements/1.1/creator
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#3D_Digital_Twin___ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#3D_Digital_Twin___BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#3D_Digital_Twin____DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#3D_Mesh_of__ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#3D_Mesh_of___of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#ACQUISITION_of_AF_MNM_005__ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#AF_MNM_005_PROCESSING_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Coordinates_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_DESCRIPTION_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#AcquisitionDevice_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#AcquisitionDevice_for_BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#AcquisitionDevice_for_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#AcquisitionDeviceType_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#AcquisitionDeviceType_for_BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#AcquisitionDeviceType_for_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Location_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Method_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Method_of__BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Method_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_of_NO01_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_of_TBZ._K._BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Phase_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Phase_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Raw_Data_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Raw_Data_of__BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Raw_Data_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Software_for_BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Software_for_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Trajectory_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Trajectory_of__BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Acquisition_Trajectory_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Color_Balance_Texture_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Dense_Point_Cloud_Mesaurement_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Dense_Point_Cloud_of__ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Dense_Point_Cloud_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Dense_Point_Cloud:_Depth_Noise_Filtering_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Densification_Alghoritm_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Densification_Method_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Densification_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Densification_of_DELTArmA001.
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#DigitalScale_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Eidotype_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Final_Use_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#GeometryType_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#GeometryType_for_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Implementation_in_Pject_BeaVIR_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Interactive_Software_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#interactive_software_for_BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Matching_Algorithm_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Matching_Method_of__DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Matching_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Matching_of_BETAfs001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Matching_of_NO01__DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Mesh_Reconstruction_of_AFMNM005
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Mesh_Reconstruction_of_NO01_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Modelling_3D_Mesh_of_NO01_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Modelling_Date_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Modelling_Description_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#ModellingDetemination_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Modelling_Device_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#ModellingElimination_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Modelling_of_AFMNM005_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Modelling_of_NO01_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Modelling_Operator_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Modelling_Software_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Number_of_Picture_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Number_of_Point_Dense_Point_Cloud_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Number_of_TExture_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Picture_Set__of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Picture_Set__of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Pocessing_Software_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Pocessing_Software_for_BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Pocessing_Software_for_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Point_Cloud_of__ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Point_Cloud_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Processing_Device_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Processing_Device_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Processing_of_NO01_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Processing_of_TBZ._K._BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#processing_operator_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Processing_Phase_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Processing_Phase_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Reconstruction_Algorithm_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Reconstruction_Algorithm_for_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Reconstruction_Method_of__DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Scale_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Scale_for_BETAfs001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Scale_for_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Smoothing_Filter_of_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Survey_Date_of_AFMNM005_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Survey_OPERATOR_of_AFMNM005_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Survey_Object_for__ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Survey_Object_for__BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Survey_Object_for__DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Textured_3D_Mesh_of__ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Textured_3D_Mesh_of_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Texturing_Mesh_of_NO01__DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Texturing_Method_of__DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Texturing_Type_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#Texturing_Type_DELTArmA001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#TrajectoryType_for_ALFAfsB001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#TrajectoryType_for_BETAfsF001
IRI: http://www.semanticweb.org/vitto/ontologies/2024/9/PODS_1#TrajectoryType_for_DELTArmA001
The authors would like to thank Silvio Peroni for developing LODE, a Live OWL Documentation Environment, which is used for representing the Cross Referencing Section of this document and Daniel Garijo for developing Widoco, the program used to create the template used in this documentation.