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Enriching 3D Collections

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.de

© Fraunhofer IGD
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 network

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    © Fraunhofer IGD
Workflow with 3D collections




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    © Fraunhofer IGD
Workflow with 3D collections




4
    © Fraunhofer IGD
Workflow with 3D collections

                        Accessing:
                       search and browse




5
    © Fraunhofer IGD
Workflow with 3D collections

                        Accessing:
                       search and browse




6
    © Fraunhofer IGD
Building a 3D collection




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    © Fraunhofer IGD
Multimedia Information
                Collections management   Conservation




                                            Images
                       Bibliographic

8
    © Fraunhofer IGD
Digitization

     3D geometry
     Material properties
     Digital provenance




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    © Fraunhofer IGD
Processing

      Improve the quality of 3D artifacts
      Process 3D artifacts for different purposes (e.g. research,
       presentation)




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     © Fraunhofer IGD
Provenance

        Legacy and rich processing metadata



                                                                 used_as_derivation_source
                                          A.15-1955-dome-out.zip                                       used_as_derivation_source
                   IvoryPanel
     3IvoPan_LegacyData.rdf                                                                                                                                2009CA5307v
                                                                                                                                                           Coloured.ply
                                                                   4Ivory_Arc3DPro           Arc3D-A.15-1955_dmy.v3d            5Ivory_MeshLa
                                                                   cEvent.rdf                                                   bProcEvent.rdf
                                               has_created                                                                                           created_derivative
        digitized                                                                created_derivative
                                                                                                                                        Legend
                                    A.15-1955-dome-
                     forms_part_o   out.rdf
                           f                                                 2009CR4851_0.rdf          has_created                               Digitization_Process
1IvoryPanel_O
bjAcqEvent.rdf                                               forms_part_o               …                            2009CR4851_0.tif            Formal_Derivation
                                                                   f         2009CA5306_0.rdf
                                                                                                                         …
                    forms_part_o     2IvoryPanel_            forms_part_o                                                                        Sub-events
                          f          DocEvent.rdf                  f                               has_created   2009CA5306_0.tif
                                                                                                                                                 Data_Object

                                                                                                                                                 Man_Made_Object




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       © Fraunhofer IGD
Ingestion

      Individual objects with high-    Large acquisition campaigns
       quality metadata                  with similar structures




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     © Fraunhofer IGD
Accessing a 3D collection

                         Accessing:
                        search and browse




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     © Fraunhofer IGD
Metadata Accessing

     Stanford Repository
      3D artifacts without
       searchable metadata




                              http://www-graphics.stanford.edu/data/3Dscanrep/

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     © Fraunhofer IGD
Metadata Accessing

     AIM@SHAPE
      3D artifacts with basic
       searchable metadata,
       e.g. categories, keywords




                                   http://shapes.aim-at-shape.net/

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     © Fraunhofer IGD
Metadata Accessing

     3D-COFORM
      3D artifacts with rich
       metadata
      Fundamental
       categories and
       relationships
      Searchable material
       and shape properties




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     © Fraunhofer IGD
User Accessing

     Administrator




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     © Fraunhofer IGD
User Accessing

     CH professional




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     © Fraunhofer IGD
User Accessing

     Internet user




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     © Fraunhofer IGD
Enriching a 3D collection




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     © Fraunhofer IGD
3D Shape Annotation

Aim: associate digital 3D shapes with related information and
 knowledge on the represented object
Annotation: mechanism for enriching digital 3D shapes with
 semantics
Result: annotated shape or a semantically enriched shape,
 combining:
 the geometric description
 contextual information
 knowledge of the represented object
 the created relationships


© Fraunhofer IGD
Sponsors

Projects:
 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
Annotation Process




© Fraunhofer IGD
Annotation Process




© Fraunhofer IGD
Geometric Definition

Aim:
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
Geometric Definition

Techniques:
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
Geometric Definition

Principles:

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
Geometric Definition

Strategies:
Hierarchical segmentation (Shapira et al. 2010 [13],
 Wang et al. 2011 [14], Ho and Chuang 2011 [15])




© Fraunhofer IGD
Geometric Definition

Strategies:
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
Geometric Definition

Strategies:
 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
Geometric Definition

Strategies:
 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
Geometric Definition

Strategies:
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
Geometric Definition

Strategies:
Segmentation refinement (Klaplansky and Tal 2009
 [28]).




© Fraunhofer IGD
Geometric Definition

Specific 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
Geometric Definition

Challenges:
Difficult to generate a plausible and context-aware
 geometric definition for different classes of objects.
The current strategies cannot easily be mapped to the
 different applications’ requirements within a given domain.
There are few approaches trying to map principles to specific
 applications’ requirements.
A combination of principles, strategies and user guidance
 could generate the expected results.


© Fraunhofer IGD
Annotation Process




© Fraunhofer IGD
Structured Information and
Knowledge
There 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
Structured Information and
Knowledge
Structured Information for describing the intrinsic
  structure of the digital 3D shape (Papaleo and De
  Floriani 2010 [26], Attene et al. 2009 [16]).




© Fraunhofer IGD
Structured Information and
Knowledge
Structured 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
Structured Information and
Knowledge
Structured 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
Structured Information and
Knowledge
Structured 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
Annotation Process




© Fraunhofer IGD
Mechanisms for Annotating

Different 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
Mechanisms for Annotating

Application 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
Mechanisms for Annotating

User 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
Mechanisms for Annotating

Supporting 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
Annotation Process




© Fraunhofer IGD
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
Representation of the Annotation

Strategies: 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
Representation of the Annotation

Strategies: 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
Representation of the Annotation

Issues:
 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
Enriching a 3D collection

Challenges and Opportunities
This 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
Enriching a 3D collection

Challenges and Opportunities
Opportunities 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
Workflow with 3D collections

                         Accessing:
                        search and browse




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     © Fraunhofer IGD
Enabling Technologies

     Cloud Computing
      Storage and computation                   Cloud
       capacity online
                                               Computing
     3D Internet
      Visualization of 3D artifacts on
       standard web browsers
     Mobile devices                       Mobile         3D
      Access and visualization on the    devices     Internet
       move



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     © Fraunhofer IGD
Emerging Challenges

      Define workflows
      Create services
      Enable intuitive access
      Provide contextualized interfaces


     User involvement and engagement




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     © Fraunhofer IGD
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
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
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
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.de
60
     © Fraunhofer IGD
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
          relationships

61
     © Fraunhofer IGD
IVB: Searching and Browsing
     Interface




                                   multimedia results
Querying 3D
 collections




                                       Exploring
62
     © Fraunhofer IGD
63
                         Inspecting and tagging
                               3D models




© Fraunhofer IGD
                                                  Interface
                                                  IVB: Viewing and Annotating




                        Enriching 3D with
                        multimedia objects

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S. Pena Serna - Enriching

  • 1. Enriching 3D Collections 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.de © Fraunhofer IGD
  • 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 network 2 © Fraunhofer IGD
  • 3. Workflow with 3D collections 3 © Fraunhofer IGD
  • 4. Workflow with 3D collections 4 © Fraunhofer IGD
  • 5. Workflow with 3D collections Accessing: search and browse 5 © Fraunhofer IGD
  • 6. Workflow with 3D collections Accessing: search and browse 6 © Fraunhofer IGD
  • 7. Building a 3D collection 7 © Fraunhofer IGD
  • 8. Multimedia Information Collections management Conservation Images Bibliographic 8 © Fraunhofer IGD
  • 9. Digitization  3D geometry  Material properties  Digital provenance 9 © Fraunhofer IGD
  • 10. Processing  Improve the quality of 3D artifacts  Process 3D artifacts for different purposes (e.g. research, presentation) 10 © Fraunhofer IGD
  • 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 2009CA5307v Coloured.ply 4Ivory_Arc3DPro Arc3D-A.15-1955_dmy.v3d 5Ivory_MeshLa cEvent.rdf bProcEvent.rdf has_created created_derivative digitized created_derivative Legend A.15-1955-dome- forms_part_o out.rdf f 2009CR4851_0.rdf has_created Digitization_Process 1IvoryPanel_O bjAcqEvent.rdf forms_part_o … 2009CR4851_0.tif Formal_Derivation f 2009CA5306_0.rdf … forms_part_o 2IvoryPanel_ forms_part_o Sub-events f DocEvent.rdf f has_created 2009CA5306_0.tif Data_Object Man_Made_Object 11 © Fraunhofer IGD
  • 12. Ingestion  Individual objects with high-  Large acquisition campaigns quality metadata with similar structures 12 © Fraunhofer IGD
  • 13. Accessing a 3D collection Accessing: search and browse 13 © Fraunhofer IGD
  • 14. Metadata Accessing Stanford Repository  3D artifacts without searchable metadata http://www-graphics.stanford.edu/data/3Dscanrep/ 14 © Fraunhofer IGD
  • 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. Metadata Accessing 3D-COFORM  3D artifacts with rich metadata  Fundamental categories and relationships  Searchable material and shape properties 16 © Fraunhofer IGD
  • 17. User Accessing Administrator 17 © Fraunhofer IGD
  • 18. User Accessing CH professional 18 © Fraunhofer IGD
  • 19. User Accessing Internet user 19 © Fraunhofer IGD
  • 20. Enriching a 3D collection 20 © Fraunhofer IGD
  • 21. 3D Shape Annotation Aim: associate digital 3D shapes with related information and knowledge on the represented object Annotation: mechanism for enriching digital 3D shapes with semantics Result: annotated shape or a semantically enriched shape, combining:  the geometric description  contextual information  knowledge of the represented object  the created relationships © Fraunhofer IGD
  • 22. Sponsors Projects:  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
  • 25. Geometric Definition Aim: 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. Geometric Definition Techniques: 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. Geometric Definition Principles: 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. Geometric Definition Strategies: Hierarchical segmentation (Shapira et al. 2010 [13], Wang et al. 2011 [14], Ho and Chuang 2011 [15]) © Fraunhofer IGD
  • 29. Geometric Definition Strategies: 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. Geometric Definition Strategies:  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. Geometric Definition Strategies:  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. Geometric Definition Strategies: 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. Geometric Definition Strategies: Segmentation refinement (Klaplansky and Tal 2009 [28]). © Fraunhofer IGD
  • 34. Geometric Definition Specific 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. Geometric Definition Challenges: Difficult to generate a plausible and context-aware geometric definition for different classes of objects. The current strategies cannot easily be mapped to the different applications’ requirements within a given domain. There are few approaches trying to map principles to specific applications’ requirements. A combination of principles, strategies and user guidance could generate the expected results. © Fraunhofer IGD
  • 37. Structured Information and Knowledge There 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. Structured Information and Knowledge Structured 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. Structured Information and Knowledge Structured 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. Structured Information and Knowledge Structured 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. Structured Information and Knowledge Structured 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
  • 43. Mechanisms for Annotating Different 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. Mechanisms for Annotating Application 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. Mechanisms for Annotating User 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. Mechanisms for Annotating Supporting 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
  • 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. Representation of the Annotation Strategies: 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. Representation of the Annotation Strategies: 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. Representation of the Annotation Issues:  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. Enriching a 3D collection Challenges and Opportunities This 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. Enriching a 3D collection Challenges and Opportunities Opportunities 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. Workflow with 3D collections Accessing: search and browse 54 © Fraunhofer IGD
  • 55. Enabling Technologies Cloud Computing  Storage and computation Cloud capacity online Computing 3D Internet  Visualization of 3D artifacts on standard web browsers Mobile devices Mobile 3D  Access and visualization on the devices Internet move 55 © Fraunhofer IGD
  • 56. Emerging Challenges  Define workflows  Create services  Enable intuitive access  Provide contextualized interfaces User involvement and engagement 56 © Fraunhofer IGD
  • 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
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  • 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.de 60 © Fraunhofer IGD
  • 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 relationships 61 © Fraunhofer IGD
  • 62. IVB: Searching and Browsing Interface multimedia results Querying 3D collections Exploring 62 © Fraunhofer IGD
  • 63. 63 Inspecting and tagging 3D models © Fraunhofer IGD Interface IVB: Viewing and Annotating Enriching 3D with multimedia objects