Enriching 3D Collections


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Enriching 3D Collections

  1. 1. Enriching 3D CollectionsSebastian Pena Serna Fraunhofer-Institut für Graphische Datenverarbeitung IGD Fraunhoferstraße 5 64283 Darmstadt Tel +49 6151 155 – 468 sebastian.pena.serna@igd.fraunhofer.de www.igd.fraunhofer.de© Fraunhofer IGD
  2. 2. Definitions 3D Collection  Digital archive with multimedia material and 3D artifacts, which is associated with semantic information Building  Acquisition and ingestion of digital assets and their corresponding provenance information Accessing  Browsing and exploration of digital assets in the 3D collection Enriching  Increasing the associations within the semantic network2 © Fraunhofer IGD
  3. 3. Workflow with 3D collections3 © Fraunhofer IGD
  4. 4. Workflow with 3D collections : s d ing roces uil and p Be q uir ac4 © Fraunhofer IGD
  5. 5. Workflow with 3D collections Accessing: search and browse : s d ing roces uil and p Be q uir ac5 © Fraunhofer IGD
  6. 6. Workflow with 3D collections Accessing: search and browse : s vie En d ing roces w ric an h uil and p Be d in an g uir no : q ta ac te6 © Fraunhofer IGD
  7. 7. Building a 3D collection : s d ing roces uil and p Be q uir ac7 © Fraunhofer IGD
  8. 8. Multimedia Information Collections management Conservation Images Bibliographic8 © Fraunhofer IGD
  9. 9. Digitization  3D geometry  Material properties  Digital provenance9 © Fraunhofer IGD
  10. 10. Processing  Improve the quality of 3D artifacts  Process 3D artifacts for different purposes (e.g. research, presentation)10 © Fraunhofer IGD
  11. 11. Provenance  Legacy and rich processing metadata used_as_derivation_source A.15-1955-dome-out.zip used_as_derivation_source IvoryPanel 3IvoPan_LegacyData.rdf 3IvoPan_LegacyData.rdf 2009CA5307v Coloured.ply 4Ivory_Arc3DPro 4Ivory_Arc3DPro Arc3D-A.15-1955_dmy.v3d 5Ivory_MeshLa 5Ivory_MeshLa cEvent.rdf cEvent.rdf bProcEvent.rdf bProcEvent.rdf has_created created_derivative digitized created_derivative Legend A.15-1955-dome- A.15-1955-dome- forms_part_of out.rdf out.rdf 2009CR4851_0.rdf 2009CR4851_0.rdf has_created Digitization_Process1IvoryPanel_Ob 1IvoryPanel_ObjAcqEvent.rdf jAcqEvent.rdf forms_part_of … 2009CR4851_0.tif Formal_Derivation 2009CA5306_0.rdf 2009CA5306_0.rdf … forms_part_of 2IvoryPanel_ 2IvoryPanel_ forms_part_of Sub-events DocEvent.rdf DocEvent.rdf has_created 2009CA5306_0.tif Data_Object Man_Made_Object11 © Fraunhofer IGD
  12. 12. Ingestion  Individual objects with high-  Large acquisition campaigns quality metadata with similar structures12 © Fraunhofer IGD
  13. 13. Accessing a 3D collection Accessing: search and browse13 © Fraunhofer IGD
  14. 14. Metadata Accessing Stanford Repository  3D artifacts without searchable metadata http://www-graphics.stanford.edu/data/3Dscanrep/14 © Fraunhofer IGD
  15. 15. Metadata Accessing AIM@SHAPE  3D artifacts with basic searchable metadata, e.g. categories, keywords http://shapes.aim-at-shape.net/15 © Fraunhofer IGD
  16. 16. Metadata Accessing 3D-COFORM  3D artifacts with rich metadata  Fundamental categories and relationships  Searchable material and shape properties16 © Fraunhofer IGD
  17. 17. User Accessing Administrator17 © Fraunhofer IGD
  18. 18. User Accessing CH professional18 © Fraunhofer IGD
  19. 19. User Accessing Internet user19 © Fraunhofer IGD
  20. 20. Enriching a 3D collection vie En w ric an h d in an g no : ta te20 © Fraunhofer IGD
  21. 21. 3D Shape AnnotationAim: associate digital 3D shapes with related information and knowledge on the represented objectAnnotation: mechanism for enriching digital 3D shapes with semanticsResult: annotated shape or a semantically enriched shape, combining: the geometric description contextual information knowledge of the represented object the created relationships© Fraunhofer IGD
  22. 22. SponsorsProjects: AIM@SHAPE (http://www.aimatshape.net/) Focus K3D (http://www.focusk3d.eu/) 3D-COFORM (www.3d-coform.eu) V-MusT (http://www.v-must.net/) Enhancing Engagement with 3D Heritage Data through Semantic Annotation ( http://www.ddsgsa.net/projects/empire/Empire/Home.html) Semantic Annotations for 3D Artefacts (http://itee.uq.edu.au/~eresearch/projects/3dsa)Technologies: Linking Open Data ( http://esw.w3.org/SweoIG/TaskForces/CommunityProjects/LinkingOpenData) 3D Internet (Alpcan et al. 2007 [33])© Fraunhofer IGD
  23. 23. Annotation Process© Fraunhofer IGD
  24. 24. Annotation Process© Fraunhofer IGD
  25. 25. Geometric DefinitionAim: Understand the intrinsic structure of the digital 3D shape (Attene et al. 2006 [1], De Floriani et al. 2010 [2]) Associate semantics with relevant part(s) of the digital 3D shape (Spagnuolo and Felcidieno 2009 [3])© Fraunhofer IGD
  26. 26. Geometric DefinitionTechniques: Sketching, painting, outlining, fitting, segmenting, and structuring These are driven by different principles (Attene at al. 2006 [4], Shamir 2008 [5] and Chen et al. 2009 [6])© Fraunhofer IGD
  27. 27. Geometric DefinitionPrinciples: RANSAC (Schnabel et al. 2007 [7]) Curvature analysis (Madeira et al. 2007 [8]) Contour analysis (Liu and Zhang 2007 [9]) Discrete operators (Reuter et al. 2009 [10]) Physics (Fang et al. 2011 [11]) Concavity (Au et al. 2011 [12])© Fraunhofer IGD
  28. 28. Geometric DefinitionStrategies:Hierarchical segmentation (Shapira et al. 2010 [13], Wang et al. 2011 [14], Ho and Chuang 2011 [15])© Fraunhofer IGD
  29. 29. Geometric DefinitionStrategies: Combination of geometric principles with other concepts about the represented shape (Attene et al. 2009 [16], Golovinsliy and Fankhouser 2009 [17], Kalogerakis et al. 2010 [18]).© Fraunhofer IGD
  30. 30. Geometric DefinitionStrategies: Skeletons to identify the structure of the digital 3D (Tierny et al. 2007 [19], Shapira et al. 2008 [20]) and/or by means of fitting primitives (Attene et al. 2006 [21]).© Fraunhofer IGD
  31. 31. Geometric DefinitionStrategies: User assisted segmentation for complex digital 3D shapes or for additional requirements, e.g. functions or styles (De Floriani et al. 2008 [22], Miao et al. 2009 [23], Bergamasco et al. 2011 [24]).© Fraunhofer IGD
  32. 32. Geometric DefinitionStrategies:Manual segmentation, sketching (Ji et al. 2006 [25]), painting (Papaleo and De Floriani 2010 [26]) or outlining regions (Pena Serna et al. 2011 [27]).© Fraunhofer IGD
  33. 33. Geometric DefinitionStrategies:Segmentation refinement (Klaplansky and Tal 2009 [28]).© Fraunhofer IGD
  34. 34. Geometric DefinitionSpecific Requirements:Scenes (Knopp et al. 2011 [29])Developable segments (Julius et al. 2005 [30])Best view (Mortara and Spagnuolo 2009 [31]).Identify adjectives (Simari et al. 2009 [32])© Fraunhofer IGD
  35. 35. Geometric DefinitionChallenges:Difficult to generate a plausible and context-aware geometricdefinition for different classes of objects.The current strategies cannot easily be mapped to the differentapplications’ requirements within a given domain.There are few approaches trying to map principles to specificapplications’ requirements.A combination of principles, strategies and user guidance couldgenerate the expected results.© Fraunhofer IGD
  36. 36. Annotation Process© Fraunhofer IGD
  37. 37. Structured Information and KnowledgeThere is a vast amount of existent information and knowledge related to any digital 3D shape:Information related to the intrinsic structure of the 3D shapeInformation related to the meaning of the represented objectInformation related to the digital provenanceKnowledge related to the application domain© Fraunhofer IGD
  38. 38. Structured Information and KnowledgeStructured Information for describing the intrinsic structure of the digital 3D shape (Papaleo and De Floriani 2010 [26], Attene et al. 2009 [16]).© Fraunhofer IGD
  39. 39. Structured Information and KnowledgeStructured Information for describing digital 3D shapes using concepts within a particular domain (Catalano et al. 2009 [34], De Luca et al. 2011 [35], Mortara et al. 2006 [36]).© Fraunhofer IGD
  40. 40. Structured Information and KnowledgeStructured Information in the engineering domain Product and Manufacturing Information (PMI) Geometric Dimensions and Tolerances (GD&T) Functional Tolerancing and Annotation (FT&A). Standard ASME Y14.41-2003 Digital Product Data Definition Practices ISO 1101:2004 Geometrical Product Specifications (GPS) - Geometrical tolerancing. (Spatial Corp.)© Fraunhofer IGD
  41. 41. Structured Information and KnowledgeStructured Information in the Cultural Heritage domain based on CIDOC-CRM http://cidoc.ics.forth.gr/ (Rodriguez- Echavarria et al. 2009 [37], Havemann et al. 2009 [38]).© Fraunhofer IGD
  42. 42. Annotation Process© Fraunhofer IGD
  43. 43. Mechanisms for AnnotatingDifferent mechanisms have been proposed, which vary depending on:application domaindegree of user intervention that they requiretechnology supporting themdegree of structured information which they involve.© Fraunhofer IGD
  44. 44. Mechanisms for AnnotatingApplication domain Product design (Andre and Sorito 2002 [39]) Architecture (Pittarello and Gatto 2011 [40]) Cultural Heritage (Hunter and Gerber 2010 [41]) Chemistry (Gawronski and Dumontier 2011 [42]) Medicine (Trzupek et al. 2011 [43])© Fraunhofer IGD
  45. 45. Mechanisms for AnnotatingUser interventionSemi-automatic mechanisms normally require of a degree of user intervention to define an annotation (Shapira et al. 2010 [13], Kalogerakis et al. 2010 [18]).© Fraunhofer IGD
  46. 46. Mechanisms for AnnotatingSupporting technology:stand-alone modeling systemsstand-alone 3D viewers Siemens NX (Pena Serna et al. 2011 [27])web based viewers (Hunter et al. 2010 [44])© Fraunhofer IGD
  47. 47. Annotation Process© Fraunhofer IGD
  48. 48. Representation of the AnnotationApproach to structure, store and transmit the annotating process outputImportant for the annotation’s indexing, retrieval and reutilization.There is no agreed format for this.© Fraunhofer IGD
  49. 49. Representation of the AnnotationStrategies: Persistent annotationsStore the annotation in a database based on a semantic model.The model describes the associations or relations between different media ([16], [27], Hunter et al. 2010 [45]).© Fraunhofer IGD
  50. 50. Representation of the AnnotationStrategies: Transient annotations Store and transmit annotations in a data file.  MPEG-7 (Bilasco et al. 2006 [46])  VRML / X3D (Pittarello and Faveri 2006 [47], [40], [26])  Jupiter (JT) Data Format  Product Representation Compact (PRC) Data Format  COLLADA ([37], [38])  Universal 3D Data Format  ASME Y14.41 Digital Product Definition Data Practices© Fraunhofer IGD
  51. 51. Representation of the AnnotationIssues: Stability, flexibility and easy of use There is no notion of annotation representation. It is considered as a piece of text, which is stored in a database or as a tag on a digital 3D shape. Annotations’ interoperability Degree of independency from transient digital 3D shapes.© Fraunhofer IGD
  52. 52. Enriching a 3D collectionChallenges and OpportunitiesThis remains an active area of research. Different challenges need to be solved to fully support a semantic enrichment pipeline: Automatically extracting information from a digital 3D shape Modeling semantic information Automatically linking it to the digital 3D shape Using standards to store, interoperate, and preserve annotations in the long term© Fraunhofer IGD
  53. 53. Enriching a 3D collectionChallenges and OpportunitiesOpportunities of using semantically aware 3D shapes: searching 3D shapes intelligently interacting with semantically aware 3D shapes shape matching or deriving meaning of new shapes high-level editing goal oriented 3D synthesizing knowledge management semantic visualization and interaction© Fraunhofer IGD
  54. 54. Workflow with 3D collections Accessing: search and browse : s vie En d ing roces w ric an h uil and p Be d in an g uir no : q ta ac te54 © Fraunhofer IGD
  55. 55. Enabling Technologies Cloud Computing  Storage and computation capacity online 3D Internet  Visualization of 3D artifacts on standard web browsers Mobile devices  Access and visualization on the move55 © Fraunhofer IGD
  56. 56. Emerging Challenges  Define workflows  Create services  Enable intuitive access  Provide contextualized interfaces User involvement and engagement56 © Fraunhofer IGD
  57. 57. References [1] ATTENE M., BIASOTTI S., MORTARA M., PATANÉ G., SPAGNUOLO M., FALCIDIENO B.: Computational methods for understanding 3D shapes. Computers & Graphics 30, 3 (June 2006), 323–333. [2] DE FLORIANI L., MAGILLO P., PAPALEO L., PUPPO E.: Shape modeling and understanding: Research trends and results of the G3 group at DISI. [3] SPAGNUOLO M., FALCIDIENO B.: 3D media and the semantic web. IEEE Intelligent Systems (March/April 2009), 90–96. [4] ATTENE M., KATZ S., MORTARA M., PATANÉ G., SPAGNUOLO M., TAL A.: Mesh segmentation - a comparative study. In Shape Modeling International (2006). [5] SHAMIR A.: A survey on mesh segmentation techniques. Computer Graphics Forum 27, 6 (2008), 1539–1556. [6] CHEN X., GOLOVINSKIY A., FUNKHOUSER T.: A benchmark for 3D mesh segmentation. In ACM SIGGRAPH 2009 papers (New Orleans, Louisiana, 2009), ACM, pp. 1– 12. [7] SCHNABEL R., WAHL R., KLEIN R.: Efficient RANSAC for Point-Cloud shape detection. Computer Graphics forum 26, Number 2 (June 2007), 214–226. [8] MADEIRA J., SILVA S., STORK A., PENA SERNA S.: Principal Curvature-Driven segmentation of mesh models: A preliminary assessment. In 15 EPCG - Encontro Português de Computação Gráfica. (2007). [9] LIU R., ZHANG H.: Mesh segmentation via spectral embedding and contour analysis. Volume 26 (2007), Number 3. [10] REUTER M., BIASOTTI S., GIORGI D., PATANÉ G., SPAGNUOLO M.: Discrete Laplace-Beltrami operators for shape analysis and segmentation. Computers & Graphics 33, 3 (June 2009), 381–390. [11] FANG Y., SUN M., KIM M.: Heat-Mapping: a robust approach toward perceptually consistent mesh segmentation. IEEE Computer Vision and Pattern Recognition (CVPR) 2011 (2011), pp 2145–2152. [12] AU O. K., ZHENG Y., CHEN M., XU P., TAI C.: Mesh segmentation with concavity-aware fields. IEEE Trans. Vis. Comp. Graphics (2011). [13] SHAPIRA L., SHALOM S., SHAMIR A., COHEN-OR D., ZHANG H.: Contextual part analogies in 3D objects. Int. J. Comput. Vision 89, 2-3 (2010), 309–326. [14] WANG Y., XU K., LI J., ZHANG H., SHAMIR A., LIU L., CHENG Z., XIONG Y.: Symmetry hierarchy of Man-Made objects. Computer Graphics Forum 30, 2 (2011), 287– 296. [15] HO T., CHUANG J.: Volume based mesh segmentation. Journal of Information Science and Engineering 27 (2011). [16] ATTENE M., ROBBIANO F., SPAGNUOLO M., FALCIDIENO B.: Characterization of 3D shape parts for semantic annotation. Computer-Aided Design 41, 10 (Oct. 2009), 756–763. [17] GOLOVINSKIY A., FUNKHOUSER T.: Consistent segmentation of 3D models. Computers & Graphics 33, 3 (June 2009), 262–269. [18] KALOGERAKIS E., HERTZMANN A., SINGH K.: Learning 3D Mesh Segmentation and Labeling. ACM Transactions on Graphics 29, 3 (2010).© Fraunhofer IGD
  58. 58. References [19] TIERNY J., VANDEBORRE J.-P., DAOUDI M.: Topology driven 3d mesh hierarchical segmentation. In Proceedings of the IEEE International Conference on Shape Modeling and Applications 2007 (Washington, DC, USA, 2007), IEEE Computer Society, pp. 215–220. [20] SHAPIRA L., SHAMIR A., COHEN-OR D.: Consistent mesh partitioning and skeletonisation using the shape diameter function. The Visual Computer: International Journal of Computer Graphics 24, 4 (Mar. 2008). [21] ATTENE M., FALCIDIENO B., SPAGNUOLO M.: Hierarchical mesh segmentation based on fitting primitives. The Visual Computer: International Journal of Computer Graphics 22 (2006), 181–193. [22] DE FLORIANI L., PAPALEO L., CARISSIMI N.: A Java3D framework for inspecting and segmenting 3D models. In Proceedings of the 13th international symposium on 3D web technology (Los Angeles, California, 2008), ACM, pp. 67–74. [23] MIAO Y., FENG J., WANG J., JIN X.: User-controllable mesh segmentation using shape harmonic signature. Progress in Natural Science 19, 4 (Apr. 2009), 471–478. [24] BERGAMASCO F., ALBARELLI A., TORSELLO A.: Semi-supervised segmentation of 3D surfaces using a weighted graph representation. In Proceedings of the 8th international conference on Graph-based representations in pattern recognition (GbRPR’11) (2011). [25] JI Z., LIU L., CHEN Z., WANG G.: Easy mesh cutting. Computer Graphics Forum 25, 3 (2006), 283–291. [26] PAPALEO L., DE FLORIANI L.: Manual segmentation and semantic-based hierarchical tagging of 3D models. (2010) pp. 25–32. [27] PENA SERNA S., SCOPIGNO R., DOERR M., THEODORIDOU M., GEORGIS C., PONCHIO F., STORK A.: 3D-centered media linking and semantic enrichment through integrated searching, browsing, viewing and annotating. In VAST11: The 12th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage (Prato, Italy, 2011). [28] KAPLANSKY L., TAL A.: Mesh segmentation refinement. In Computer Graphics Forum (Pacific Graphics), 28(7) (Oct. 2009), pp. 1995–2003. [29] KNOPP J., PRASAD M. , VAN GOOL L. : Scene Cut: Class-specific Object Detection and Segmentation in 3D Scenes. In 3DIMPVT, Hangzhou, 2011 [30] JULIUS D., KRAEVOY V., SHEFFER A.: D-charts: Quasi-developable mesh segmentation. In Computer Graphics Forum, Proceedings of Eurographics 2005 (Dublin, Ireland, 2005), vol. 24, Eurographics, Blackwell, pp. 581–590. [31] MORTARA M., SPAGNUOLO M.: Semantics-driven best view of 3D shapes. Computers & Graphics 33, 3 (June 2009), 280–290. [32] SIMARI P., NOWROUZEZAHRAI D., KALOGERAKIS E., SINGH K.: Multi-objective shape segmentation and labeling. In Proceedings of the Symposium on Geometry Processing (Berlin, Germany, 2009), Eurographics Association, pp. 1415–1425. [33] ALPCAN T., BAUCKHAGE C., KOTSOVINOS E.: Towards 3d internet: Why, what, and how? In Proceedings of the International Conference on Cyberworlds CW ’07 (October 2007), pp. 95 – 99. [34] CATALANO C., CAMOSSI E., FERRANDES R., CHEUTET V., SEVILMIS N.: A product design ontology for enhancing shape processing in design workflows. Journal of Intelligent Manufacturing 20, 5 (Oct. 2009), 553–567. 3© Fraunhofer IGD
  59. 59. References [35] LUCA L. D., BUSAYARAT C., STEFANI C., VÉRON P., FLORENZANO M.: A semantic-based platform for the digital analysis of architectural heritage. Computers & Graphics 35, 2 (Apr. 2011), 227–241. [36] MORTARA M., PATANÉ G., SPAGNUOLO M.: From geometric to semantic human body models. Computers&Graphics 30, 2 (Apr. 2006), 185–196. [37] RODRIGUEZ ECHAVARRIA K., MORRIS D., ARNOLD D.: Web based presentation of semantically tagged 3D content for public sculptures and monuments in the UK. In Proceedings of the 14th International Conference on 3D Web Technology (Darmstadt, Germany, 2009), ACM, pp. 119–126. [38] HAVEMANN S., SETTGAST V., BERNDT R., EIDE., FELLNER D. W.: The Arrigo showcase reloaded - towards a sustainable link between 3D and semantics. J. Comput. Cult. Herit. 2, 1 (2009), 1–13. [39] ANDRE P., SORITO R.: Product manufacturing information (PMI) in 3D models: a basis for collaborative engineering in product creation process (PCP). In 14th European Simulation Symposium and Exhibition (2002). [40] PITTARELLO F., GATTO I.: ToBoA-3D: an architecture for managing top-down and bottom-up annotated 3D objects and spaces on the web. In Web3D ’11 Proceedings of the 16th International Conference on 3D Web Technology (2011). [41] HUNTER J., GERBER A.: Harvesting community annotations on 3D models of museum artefacts to enhance knowledge, discovery and re-use. Journal of Cultural Heritage 11, 1 (2010), 81–90. [42] GAWRONSKI A., DUMONTIER M.: MoSuMo: a semantic web service to generate electrostatic potentials across solvent excluded protein surfaces and binding pockets. Computers & Graphics 35, 4 (Aug. 2011), 823–830. [43] TRZUPEK M., OGIELA M. R., TADEUSIEWICZ R.: Intelligent image content semantic description for cardiac 3D visualisations. Engineering Applications of Artificial Intelligence In Press, Corrected Proof (2011). [44] HUNTER J., YU C.-H., NAKATSU R., TOSA N., NAGHDY F., WONG K., CODOGNET P.: Supporting multiple perspectives on 3D museum artefacts through interoperable annotations. Vol. 333 of IFIP Advances in Information and Communication Technology. Springer Boston, 2010, pp. 149–159. [45] HUNTER J., COLE T., SANDERSON R., VAN DE SOMPEL H.: The open annotation collaboration: A data model to support sharing and interoperability of scholarly annotations. (2010) [46] BILASCO I. M., GENSEL J., VILLANOVA-OLIVER M., MARTIN H.: An MPEG-7 framework enhancing the reuse of 3D models. In Proceedings of the eleventh international conference on 3D web technology (Columbia, Maryland, 2006), ACM, pp. 65–74. [47] PITTARELLO F., FAVERI A. D.: Semantic description of 3D environments: a proposal based on web standards. In Proceedings of the eleventh international conference on 3D web technology (Columbia, Maryland, 2006), ACM, pp. 85–95.© Fraunhofer IGD
  60. 60. Thank You! Sebastian Pena Serna Fraunhofer-Institut für Graphische Datenverarbeitung IGD Fraunhoferstraße 5 64283 Darmstadt Tel +49 6151 155 – 468 sebastian.pena.serna@igd.fraunhofer.de www.igd.fraunhofer.de60 © Fraunhofer IGD
  61. 61. IVB: Integrated Viewer /Browser Access and enrichment of 3D collections  Searching and browsing  Searching: flexible formulation of queries  Browsing: exploration of multiple results and query refinement  Viewing and Annotating  Viewing: inspection and analysis of multimedia objects  Annotating: building and enrichment of semantic relationships61 © Fraunhofer IGD
  62. 62. IVB: Searching and Browsing Interface62 © Fraunhofer IGD
  63. 63. IVB: Viewing and Annotating Interface63 © Fraunhofer IGD