a hierarchical approach to motion analysis and synthesis for articulated figures
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A Hierarchical Approach to Motion Analysis and Synthesis for Articulated Figures. Jehee Lee Computer Science Department KAIST. Content. 1. Introduction 2. Spatial filtering for orientation data 3. Motion editing with spacetime constraints - PowerPoint PPT PresentationTRANSCRIPT
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A Hierarchical Approach toMotion Analysis and Synthesisfor Articulated FiguresJehee Lee
Computer Science DepartmentKAIST
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Content1. Introduction2. Spatial filtering for orientation data3. Motion editing with spacetime constraints4. Multiresolution motion analysis and synthesis5. Conclusion and Future work
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Character AnimationRealistic motion datamotion capture technologycommercial librariesProduce animation from available motion clipsrequires specialized toolsinteractive editing, smoothing, enhancement, blending, provides a great variety incharacter size, environment geometry, scenario, ...
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Motion of Articulated FiguresStructure of motion databundle of motion signalseach signal represents either position or orientationDifficulties in handling motion dataorientations yield complicationsunit quaternionsmutual relationships among motion signals
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OverviewDesigning spatial filters for motion dataMotion editing with spacetime constraintsMultiresolution motion analysis and synthesisEditing &AdaptationAnalysis &SynthesisFilteringrawinputsignalconvincinganimation ofarbitrary lengthCrafting animation from motion-captured data
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Content1. Introduction2. Spatial filtering for orientation data3. Motion editing with spacetime constraints4. Multiresolution motion analysis and synthesis5. Conclusion and Future work
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Spatial Filtering for Orientation DataLinear shift-invariant (LSI) filterfilter mask : vector-valued signal :
Not suitable for unit quaternion dataunit-length constraints
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Previous WorkBrute-force normalizationAzuma and Bishop (94)Employ exponential and logarithmic mapsLee and Shin (96)Fang et al (98)Hsieh et al (98)lack of crucial filter properties
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RequirementsAvoid brute-force normalizationSatisfy desired propertiesIndependent of coordinate systemIndependent of timeIndependent of reflection
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Basic IdeaExploit correspondence in differential spacesLinear motion : Angular motion : VelocityAcceleration
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TransformationTransformation between linear and angular signals
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Filter DesignGiven: spatial filter FOutput: spatial filter H for orientation data
filter responses of unit lengthlocally supported#support(H ) = #support(F )
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Filter DesignGiven: spatial filter FOutput: spatial filter H for orientation data
filter responses of unit lengthlocally supported#support(H ) = #support(F )
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Properties of Orientation FiltersCoordinate-invariance
Shift-invariance
Symmetry
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Experimental Results (1)Blurring by binomial masksOriginalAngular accelerationFilteredOriginalFiltered
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Experimental Results (2)SmoothingOriginalAngular accelerationFilteredOriginalFiltered
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Experimental Results (3)High-frequency boostingOriginalAngular accelerationFilteredOriginalFiltered
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VideoSmoothing and Sharpening
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Summary (Motion Filtering)A general scheme of constructing spatial filters for orientation datasatisfies desired propertiessimple, efficient, and easy to implementperforms well for live-captured data
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Content1. Introduction2. Spatial filtering for orientation data3. Motion editing with spacetime constraints4. Multiresolution motion analysis and synthesis5. Conclusion and Future work
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Motion EditingReuse available motion clipsInteractive motion editingdirect manipulation through graphical interfaceMotion adaptationnew charactersnew environmentsnew scenario
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Spacetime FormulationSpacetime constraints[Witkin and Kass 88] [Cohen 92] [Gleicher 98]important features of the original motionnew features to be accomplishedTo find a new motionsatisfying given constraintspreserving original characteristics
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Previous WorkGeometric techniquesBruderlin and Williams (95)Popovic and Witkin (95)lack of consideration on kinematic constraintsSpacetime optimizationRose et al (96)Gleicher (98)yield very large optimization that is cumbersome to handle
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VideoDirect manipulation with spacetime constraints
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Basic IdeaStructure of motion sequencesIntra-frame relationshipsatisfying constraintsby inverse kinematicsInter-frame relationshipavoiding jerkinessby curve fitting
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Motion RepresentationConfiguration of articulated figurescomprises both linear and angular components
rigid transformation
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Motion Displacement Mapping
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Adaptive RefinementFlexibility in representationspline curves over a uniform knot sequence hard to determine knot densityadaptive refinement is neededMultilevel or hierarchical B-splines[Lee, Wolberg and Shin 97] [Forsey and Bartels 95] sum of uniform B-spline functionscoarse-to-fine hierarchy of knot sequences
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Multilevel B-spline FittingSmooth initial approximation
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Multilevel B-spline FittingRefinementwith finer functions
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