Need for Semantics
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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
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Need for Semantics To exploit fully the potential of of semantic
enrichment as many properties of the real world should be represented in their virtual counterpart
We need metaphors for describing objects that are similar to what humans employ
E.g. a table= a rectangular top, 4 cylindrical legs
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Shape Annotation Documenting the 3D shape with contextual
knowledge
Knowledge related to the geometry
Knowledge related to the application domain
Knowledge related to the contentstatue, base
Restoration
Fracture lines
Erosion
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Shape AnalysisCharacterization:
Evaluation of scalar functions over the surface
Structuring:
Extraction of subparts and their spatial arrangement
Segmentation:
Identification of regions having homogeneous properties (main components or features of interest)
…
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Ontologies for Shape :Knowledge Modelling
modelling shapes and their associated semantics using knowledge formalisation mechanisms
metadata and ontologies provide the rules for linking semantics to shape or shape parts.
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DSW by AIM@SHAPE Many ontologies, different facets Annotate whole objects
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Geometric Search Engine
Based on Geometry
and Structure
Semantic Search Engine
Based on Metadata
advanced search engines for digital shapes
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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
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Automatic identification of human body parts
Plumber segmentation
Tagging human body parts
Tailor characterisation
Candidate skeletal joints
Skeleton extraction
IT’S LATE!
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ShapeAnnotator: general framework
Knowledge Base
ShapeA surface mesh
DomainAn OWL ontology
CG ToolsSegmentation Plug-ins
Shape
Annotator
Expert
Abstracted ShapeA segmented mesh
Instance
Instance
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Shape annotator Framework for part-based
annotation of 3D objects with context-dependent knowledge
IT’S LATE!
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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
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Fitting Primitives Hierarchical face clustering algorithm able to
recognise planes, cylinders and spheres
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Reeb Graph 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
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Skeletons and grasping regions
Plumber (and Tailor)
It defines a shape decomposition into connected components that are either tubular features or blob regions
Landmarks
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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 …