SCA 08: Eurographics/SIGGRAPH Symposium on Computer Animation

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https://diglib.eg.org/handle/10.2312/428

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Browsing SCA 08: Eurographics/SIGGRAPH Symposium on Computer Animation by Subject "Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Animation"

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    Real-Time Planning for Parameterized Human Motion
    (The Eurographics Association, 2008) Lo, Wan-Yen; Zwicker, Matthias; Markus Gross and Doug James
    We present a novel approach to learn motion controllers for real-time character animation based on motion capture data. We employ a tree-based regression algorithm for reinforcement learning, which enables us to generate motions that require planning. This approach is more flexible and more robust than previous strategies. We also extend the learning framework to include parameterized motions and interpolation. This enables us to control the character more precisely with a small amount of motion data. Finally, we present results of our algorithm for three different types of controllers.
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    Staggered Poses: A Character Motion Representation for Detail-Preserving Editing of Pose and Coordinated Timing
    (The Eurographics Association, 2008) Coleman, Patrick; Bibliowicz, Jacobo; Singh, Karan; Gleicher, Michael; Markus Gross and Doug James
    We introduce staggered poses - a representation of character motion that explicitly encodes coordinated timing among movement features in different parts of a character's body. This representation allows us to provide sparse, pose-based controls for editing motion that preserve existing movement detail, and we describe how to edit coordinated timing among extrema in these controls for stylistic editing. The staggered pose representation supports the editing of new motion by generalizing keyframe-based workflows to retain high-level control after local timing and transition splines have been created. For densely-sampled motion such as motion capture data, we present an algorithm that creates a staggered pose representation by locating coordinated movement features and modeling motion detail using splines and displacement maps. These techniques, taken together, enable feature-based keyframe editing of dense motion data.