Tang, J.K.T. and Leung, H. and Komura, T. and Shum, Hubert (2008) Finding Repetitive Patterns in 3D Human Motion Captured Data. Proceedings of the International Conference on Ubiquitous Information Management and Communication. pp. 396-403. ISSN 978-1-59593-993-7Full text not available from this repository. (Request a copy)
Finding repetitive patterns is important to many applications such as bioinformatics, finance and speech processing, etc. Repetitive patterns can be either cyclic or acyclic such that the patterns are continuous and distributed respectively. In this paper, we are going to find repetitive patterns in a given motion signal without prior knowledge about the type of motion. It is relatively easier to find repetitive patterns in discrete signal that contains a limited number of states by dynamic programming. However, it is impractical to identify exactly matched states in a continuous signal such as captured human motion data. A point cloud similarity of the input motion signal itself is considered and the longest similar patterns are located by tracing and extending matched posture pairs. Through pattern alignment and autoclustering, cyclic and acyclic patterns are identified. Experiment results show that our approach can locate repetitive movements with small error rates.
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|Uncontrolled Keywords:||3D human motion capture, pattern discovery, repetitive pattern, cyclic and acyclic patterns, point cloud similarity.|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Academic Departments > Worcester Business School|
|Depositing User:||Hubert Shum|
|Date Deposited:||10 May 2011 13:03|
|Last Modified:||26 Jul 2015 10:04|
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