Measurement Function Design for Visual Tracking Applications

Smith, A. W. B. and Lovell, B. C. (2006). Measurement Function Design for Visual Tracking Applications. In: Y. Tang, P. Wang, G. Lorette and D. S. Yeung, 18th International Conference on Pattern Recognition (ICPR 2006), Hong Kong, (789-792). 20-24 August, 2006. doi:10.1109/ICPR.2006.785

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Author Smith, A. W. B.
Lovell, B. C.
Title of paper Measurement Function Design for Visual Tracking Applications
Conference name 18th International Conference on Pattern Recognition (ICPR 2006)
Conference location Hong Kong
Conference dates 20-24 August, 2006
Place of Publication U.S.A.
Publisher IEEE
Publication Year 2006
Sub-type Fully published paper
DOI 10.1109/ICPR.2006.785
ISBN 0-7695-2512-0
Editor Y. Tang
P. Wang
G. Lorette
D. S. Yeung
Volume 1
Start page 789
End page 792
Total pages 4
Language eng
Abstract/Summary Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.
Subjects 280208 Computer Vision
280203 Image Processing
Keyword iris-research
nictawp1
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Q-Index Code E1
Additional Notes Digital Object Identifier 10.1109/ICPR.2006.785

 
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Created: Tue, 15 May 2007, 14:56:28 EST by Prof Brian Lovell on behalf of Social Sciences and Humanities Library Service