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ABSTRACT
Computer puppetry maps the movements of a performer to an animated character in real-time. In this article, we provide a comprehensive solution to the problem of transferring the observations of the motion capture sensors to an animated character whose size and proportion may be different from the performer's. Our goal is to map as many of the important aspects of the motion to the target character as possible, while meeting the online, real-time demands of computer puppetry. We adopt a Kalman filter scheme that addresses motion capture noise issues in this setting. We provide the notion of dynamic importance of an end-effector that allows us to determine what aspects of the performance must be kept in the resulting motion. We introduce a novel inverse kinematics solver that realizes these important aspects within tight real-time constraints. Our approach is demonstrated by its application to broadcast television performances.
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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 40
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Benjamin Schaeffer , Mark Flider , Hank Kaczmarski , Luc Vanier , Lance Chong , Yu Hasegawa-Johnson, Tele-sports and tele-dance: full-body network interaction, Proceedings of the ACM symposium on Virtual reality software and technology, October 01-03, 2003, Osaka, Japan
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Yan Gao , Lizhuang Ma , Zhihua Chen , Xiaomao Wu, Motion normalization: the preprocess of motion data, Proceedings of the ACM symposium on Virtual reality software and technology, November 07-09, 2005, Monterey, CA, USA
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David A. Forsyth , Okan Arikan , Leslie Ikemoto , James O'Brien , Deva Ramanan, Computational studies of human motion: part 1, tracking and motion synthesis, Foundations and Trends® in Computer Graphics and Vision, v.1 n.2, p.77-254, July 2006
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Shin'Ichiro Nakaoka , Atsushi Nakazawa , Fumio Kanehiro , Kenji Kaneko , Mitsuharu Morisawa , Hirohisa Hirukawa , Katsushi Ikeuchi, Learning from Observation Paradigm: Leg Task Models for Enabling a Biped
Humanoid Robot to Imitate Human Dances, International Journal of Robotics Research, v.26 n.8, p.829-844, August 2007
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