Abstract
Motion capture data could describe human motion precisely. It’s anticipated some uncapturable human motions may be generated through easily capturable motions. A method was introduced to segment motion captured data, which could cut a long motion sequence into some unique motion primitives. This method involved 14 joints of body hierarchy. Singular Value Decomposition (SVM) was used to determine how motion data dimension changed, which could identify the segmentation frame. The validity of method was verified with an 8,401 frames motion sequence from Carnegie Mellon University Motion Capture Database, and it turned out to be valid in accordance with human intuitive judgment.
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Acknowledgements
This research is supported by National Key R&D Program of China (2017YFF0206602) and Special funds for the basic R&D undertakings by welfare research institutions (522016Y-4680). The authors also appreciate the support from General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China (201510042), the State Scholarship Fund from China Scholarship Council (201208110144), the National Natural Science Foundation of China (51005016), and Fundamental Research Funds for the Central Universities, China (FRF-TP-14-026A2).
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Zhao, Yt. et al. (2019). Segmentation of Human Motion Sequence Based on Motion Primitives. In: Huang, G., Chien, CF., Dou, R. (eds) Proceeding of the 24th International Conference on Industrial Engineering and Engineering Management 2018. Springer, Singapore. https://doi.org/10.1007/978-981-13-3402-3_69
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DOI: https://doi.org/10.1007/978-981-13-3402-3_69
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