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Need for Semantics

Need for Semantics. Now models represent just the object appearance We need to represent also its Properties Roles Behaviour Services … i.e. its meaning , in a human and machine understandable way The process has to be as much automatic as possible. Need for Semantics.

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Need for Semantics

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  1. NeedforSemantics • Nowmodelsrepresent just the objectappearance • Weneedtorepresentalsoits • Properties • Roles • Behaviour • Services • … • i.e. itsmeaning, in a human and machineunderstandable way • The process has to be as much automatic as possible

  2. NeedforSemantics • To exploit fully the potentialofofsemanticenrichmentasmanypropertiesof the real world shouldberepresented in theirvirtualcounterpart • We need metaphors for describing objects that are similar to what humans employ • E.g. a table= a rectangular top, 4 cylindrical legs

  3. ShapeAnnotation • Documenting the 3D shape with contextual knowledge • Knowledgerelatedto the geometry • Knowledgerelatedto the application domain • Knowledgerelatedto the content statue, base

  4. Shape Analysis Characterization: Evaluationof scalar functionsover the surface Segmentation: Identificationofregionshavinghomogeneousproperties (maincomponents or featuresof interest) Structuring: Extractionofsubparts and theirspatialarrangement …

  5. Ontologies for Shape :Knowledge Modelling • modelling shapes and their associated semantics using knowledge formalisation mechanisms • metadata and ontologiesprovide the rules for linking semantics to shape or shape parts.

  6. DSW byAIM@SHAPE • Manyontologies, differentfacets • Annotate wholeobjects

  7. Semantic Search Engine advanced search engines for digital shapes Geometric Search Engine Based on Geometry and Structure Based on Metadata

  8. Possible scenarios for virtual worlds • semantic search for reuse: • Search among models having large geometry variations (e.g. human characters and objects) • create new VHs, reuse garments, take only interesting parts • Assistive living • Simulation of domestic environments with realistic people (e.g. with disabilities), places and danger conditions

  9. Automatic identification of human body parts Plumber segmentation Tailor characterisation Skeleton extraction Tagging human body parts Candidate skeletal joints IT’S LATE!

  10. Instance Instance Expert ShapeAnnotator: general framework Shape A surface mesh Abstracted Shape A segmented mesh Shape Annotator CG Tools Segmentation Plug-ins Domain An OWL ontology Knowledge Base

  11. Shape annotator • Framework for part-based annotation of 3D objects with context-dependent knowledge IT’S LATE!

  12. Semantic-driven segmentations • They capture semantically relevant features automatically • what is relevant in the gaming context? • IMATI segmentation methods for triangle meshes: • Fitting primitives • Reeb Graphs • Tailor • Plumber • They extract specific kind of knowledge suitable also for virtual worlds

  13. FittingPrimitives • Hierarchical face clustering algorithm able to recognise planes, cylinders and spheres

  14. ReebGraph • The topology of a shape is coded into the Reeb graph respect to f, which captures the evolution of the level sets of f on the shape

  15. Landmarks Plumber (and Tailor) It defines a shape decomposition into connected components that are either tubular features or blob regions Skeletons and grasping regions

  16. Conclusions • 3D with semantics would have high impact • Easy indexing, searching and retrieval • Efficient reuse and re-adaptation • Realistic interactions among virtual characters and objects • Analysis, segmentation, annotation, knowledge base • Still a lot of work to do • Manual annotation • No shared conceptualisation • …

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