Pose Estimation for Evaluating Standing Long Jumps via Dynamic Bayesian Networks

機構典藏 > College of Engineering > Graduate Institute & Department of Computer Science and Information Engineering > Proceeding > Item 987654321/75834

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/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:	[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	248	View/Open
Pose Estimation for Evaluating Standing Long Jumps via Dynamic Bayesian Networks.pdf		392Kb	Adobe PDF	278	View/Open