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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/75834

    Title: Pose Estimation for Evaluating Standing Long Jumps via Dynamic Bayesian Networks
    Authors: Hsu, Hui-huang;Yen, Yao-bao;Chen, Chu-song;Ho, Chun-ta
    Contributors: 淡江大學資訊工程學系
    Keywords: Dynamic Bayesian networks;Motion analysis;Pose estimation;Standing long jumps;Thinning
    Date: 2008-06
    Issue Date: 2012-04-17 22:14:00 (UTC+8)
    Publisher: N.Y.: IEEE (Institute of Electrical and Electronic Engineers)
    Abstract: A system is developed for analyzing poses in a standing long jump automatically. In the system, silhouette of the jumper is segmented from the background first. A thinning algorithm is then used to find a rough skeleton from the silhouette. Some image processing techniques are applied to make the resulted skeleton smoother and simpler. Key points are extracted from the skeleton. Finally, the dynamic Bayesian network (DBN) is used to determine the corresponding pose from the key points. The experimental result shows that pose estimation accuracy is quite good. According to the standing long jump standards, incorrect movements at different stages of the jump can thus be identified.
    Relation: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (ICDCSW '08), pp.36-41
    DOI: 10.1109/ICDCS.Workshops.2008.72
    Appears in Collections:[資訊工程學系暨研究所] 會議論文

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