Abstract
We propose a framework to reconstruct human motion based on monocular camera video and motion database. In this framework, we use silhouettes for rough motion estimation based on a set of discriminative features and search motion database to find out the exact motion clips that meet with the video content. We model motion as a first-order Markov process. The transition probabilities between motion clips are preprocessed with consideration of the continuousness and smoothness of human motion. To eliminate the discontinuities between motion clips, we also adopt a seamless motion stitch method using multiresolution analysis technique. We verify the effectiveness of our method by reconstructing trampoline sports video as an example. The reconstruction results are visually comparable to those motions obtained by a commercial motion capture system in the premise that similar motions are included in the motion database.
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Wang, R., Qiu, X., Wang, Z., Xia, S. (2006). A Video-Driven Approach to Continuous Human Motion Synthesis. In: Nishita, T., Peng, Q., Seidel, HP. (eds) Advances in Computer Graphics. CGI 2006. Lecture Notes in Computer Science, vol 4035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11784203_58
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DOI: https://doi.org/10.1007/11784203_58
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