DocumentCode
2298679
Title
Human Motion Analysis
Author
Tsai, Joseph C. ; Wong, Tzu-Lin ; Zhong, Hsing-Ying ; Chang, Shih-Ming ; Shih, Timothy K.
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Tamkang Univ., Tamsui, Taiwan
fYear
2009
fDate
7-9 July 2009
Firstpage
373
Lastpage
376
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.
Keywords
computational complexity; image matching; image segmentation; image sequences; motion estimation; video signal processing; block matching algorithm; computational complexity; cross-diamond-hexagonal search algorithm; human motion analysis; mean-shift segmentation; motion estimation technique; nonrigid object tracking; video object extraction; video sequences; Clustering algorithms; Computer science education; Filtering; Humans; Motion analysis; Motion estimation; Pervasive computing; Physics computing; Robustness; Tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Ubiquitous, Autonomic and Trusted Computing, 2009. UIC-ATC '09. Symposia and Workshops on
Conference_Location
Brisbane, QLD
Print_ISBN
978-1-4244-4902-6
Electronic_ISBN
978-0-7695-3737-5
Type
conf
DOI
10.1109/UIC-ATC.2009.107
Filename
5319210
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