Abstract
This work solves the problem of synchronizing pre-recorded human motion sequences, which show different speeds and accelerations, by using a novel dense matching algorithm. The approach is based on the dynamic programming principle that allows finding an optimal solution very fast. Additionally, an optimal sequence is automatically selected from the input data set to be a time scale pattern for all other sequences. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.
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Mozerov, M., Rius, I., Roca, X., González, J. (2006). 3D Human Motion Sequences Synchronization Using Dense Matching Algorithm. In: Franke, K., Müller, KR., Nickolay, B., Schäfer, R. (eds) Pattern Recognition. DAGM 2006. Lecture Notes in Computer Science, vol 4174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861898_49
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DOI: https://doi.org/10.1007/11861898_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44412-1
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