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Synthesizing animations of human manipulation tasks
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Source ACM Transactions on Graphics (TOG) archive
Volume 23 ,  Issue 3  (August 2004) table of contents
Proceedings of ACM SIGGRAPH 2004
SESSION: Data driven character animation table of contents
Pages: 532 - 539  
Year of Publication: 2004
ISSN:0730-0301
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Authors
Katsu Yamane  The University of Tokyo
James J. Kuffner  Carnegie Mellon University
Jessica K. Hodgins  Carnegie Mellon University
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 28,   Downloads (12 Months): 158,   Citation Count: 21
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ABSTRACT

Even such simple tasks as placing a box on a shelf are difficult to animate, because the animator must carefully position the character to satisfy geometric and balance constraints while creating motion to perform the task with a natural-looking style. In this paper, we explore an approach for animating characters manipulating objects that combines the power of path planning with the domain knowledge inherent in data-driven, constraint-based inverse kinematics. A path planner is used to find a motion for the object such that the corresponding poses of the character satisfy geometric, kinematic, and posture constraints. The inverse kinematics computation of the character's pose resolves redundancy by biasing the solution toward natural-looking poses extracted from a database of captured motions. Having this database greatly helps to increase the quality of the output motion. The computed path is converted to a motion trajectory using a model of the velocity profile. We demonstrate the effectiveness of the algorithm by generating animations across a wide range of scenarios that cover variations in the geometric, kinematic, and dynamic models of the character, the manipulated object, and obstacles in the scene.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  21

Collaborative Colleagues:
Katsu Yamane: colleagues
James J. Kuffner: colleagues
Jessica K. Hodgins: colleagues