Abstract
This paper introduces an approach to performance animation that employs a small number of inertial measurement sensors to create an easy-to-use system for an interactive control of a full-body human character. Our key idea is to construct a global model from a prerecorded motion database and utilize them to construct full-body human motion in a maximum a posteriori framework (MAP). We have demonstrated the effectiveness of our system by controlling a variety of human actions, such as boxing, golf swinging, and table tennis, in real time. One unique property of our system is its ability to learn priors from a large and heterogeneous motion capture database and use them to generate a wide range of natural poses, a capacity that has not been demonstrated in previous data-driven character posing systems.
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Liu, H., He, F., Cai, X. et al. Performance-based control interfaces using mixture of factor analyzers. Vis Comput 27, 595–603 (2011). https://doi.org/10.1007/s00371-011-0563-1
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DOI: https://doi.org/10.1007/s00371-011-0563-1