Abstract
We develop an algorithm for 3D human-pose tracking through a monocular vision. The algorithm is based on body-silhouette shape matching combined with particle-filter-based selected-region tracking in the 2D view. The selected-region tracking, combined with human-body structural data, restricts the temporal interpretation of 3D human poses to those best corresponding to the 2D silhouette shapes. The experimental results demonstrate that our approach performs real-time human-motion tracking with good quality and reasonable robustness.
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Kim, M., Joo, S., Jo, S. (2013). 3D Human-Pose Tracking through a Monocular Vision. In: Kim, JH., Matson, E., Myung, H., Xu, P. (eds) Robot Intelligence Technology and Applications 2012. Advances in Intelligent Systems and Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37374-9_24
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DOI: https://doi.org/10.1007/978-3-642-37374-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37373-2
Online ISBN: 978-3-642-37374-9
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