Human Motion Analysis
We propose a novel motion analysis algorithm by using the mean-shift segmentation and motion estimation technique. Mean shift algorithm is frequently used to extract objects from video according to its efficiency and robustness of non-rigid object tracking. For diminishing the computational complexi...
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| creator | Tsai, J.C. Tzu-Lin Wong Hsing-Ying Zhong Shih-Ming Chang Shih, T.K. |
| description | We propose a novel motion analysis algorithm by using the mean-shift segmentation and motion estimation technique. Mean shift algorithm is frequently used to extract objects from video according to its efficiency and robustness of non-rigid object tracking. For diminishing the computational complexity in searching process, an efficient block matching algorithm: cross-diamond-hexagonal search algorithm was used. In the motion analysis procedure, the stick figure of object obtained by thinning process is treated as guidance to gather the statistics of motion information. The experimental results show that the proposed method provides precise description of the behavior of object in several video sequences. |
| doi_str_mv | 10.1109/UIC-ATC.2009.107 |
| format | Conference Proceeding |
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The experimental results show that the proposed method provides precise description of the behavior of object in several video sequences.</description><subject>Clustering algorithms</subject><subject>Computer science education</subject><subject>Filtering</subject><subject>Humans</subject><subject>Motion analysis</subject><subject>Motion estimation</subject><subject>Pervasive computing</subject><subject>Physics computing</subject><subject>Robustness</subject><subject>Tracking</subject><isbn>1424449022</isbn><isbn>9781424449026</isbn><isbn>0769537375</isbn><isbn>9780769537375</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjsFKAzEQQCMiaGuPguClP7DrzCTZZI7LorZQ8bKeS5KdhUi7laYe-vcW9F3e7fGUekSoEYGfP9dd1fZdTQBcI7grNQPXsNVOO3utZmjIGMNAdKsWpXzBBWM1Nu5OPax-9mFavh9O-TAt2ynsziWXe3Uzhl2Rxb_nqn996btVtfl4W3ftpsoMp8pGcgaFMHqOkSKLwdEmG0PwGoMXPyTyiVAasgmdDEKaRzSDl5CI9Vw9_WWziGy_j3kfjuft5YwJQf8CbW45ng</recordid><startdate>200907</startdate><enddate>200907</enddate><creator>Tsai, J.C.</creator><creator>Tzu-Lin Wong</creator><creator>Hsing-Ying Zhong</creator><creator>Shih-Ming Chang</creator><creator>Shih, T.K.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200907</creationdate><title>Human Motion Analysis</title><author>Tsai, J.C. ; Tzu-Lin Wong ; Hsing-Ying Zhong ; Shih-Ming Chang ; Shih, T.K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-5b2741e21b89bb2b9e41f5c5baa831a8e8dc28c21e625c17ede239f14d8eac293</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Clustering algorithms</topic><topic>Computer science education</topic><topic>Filtering</topic><topic>Humans</topic><topic>Motion analysis</topic><topic>Motion estimation</topic><topic>Pervasive computing</topic><topic>Physics computing</topic><topic>Robustness</topic><topic>Tracking</topic><toplevel>online_resources</toplevel><creatorcontrib>Tsai, J.C.</creatorcontrib><creatorcontrib>Tzu-Lin Wong</creatorcontrib><creatorcontrib>Hsing-Ying Zhong</creatorcontrib><creatorcontrib>Shih-Ming Chang</creatorcontrib><creatorcontrib>Shih, T.K.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tsai, J.C.</au><au>Tzu-Lin Wong</au><au>Hsing-Ying Zhong</au><au>Shih-Ming Chang</au><au>Shih, T.K.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Human Motion Analysis</atitle><btitle>2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing</btitle><stitle>UICATC</stitle><date>2009-07</date><risdate>2009</risdate><spage>373</spage><epage>376</epage><pages>373-376</pages><isbn>1424449022</isbn><isbn>9781424449026</isbn><eisbn>0769537375</eisbn><eisbn>9780769537375</eisbn><abstract>We propose a novel motion analysis algorithm by using the mean-shift segmentation and motion estimation technique. Mean shift algorithm is frequently used to extract objects from video according to its efficiency and robustness of non-rigid object tracking. For diminishing the computational complexity in searching process, an efficient block matching algorithm: cross-diamond-hexagonal search algorithm was used. In the motion analysis procedure, the stick figure of object obtained by thinning process is treated as guidance to gather the statistics of motion information. The experimental results show that the proposed method provides precise description of the behavior of object in several video sequences.</abstract><pub>IEEE</pub><doi>10.1109/UIC-ATC.2009.107</doi><tpages>4</tpages></addata></record> |
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| ispartof | 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, 2009, p.373-376 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Clustering algorithms Computer science education Filtering Humans Motion analysis Motion estimation Pervasive computing Physics computing Robustness Tracking |
| title | Human Motion Analysis |
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