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
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  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
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