DocumentCode :
2031855
Title :
Feature point tracking based on RLS and MAP filter
Author :
Zhou, Yingfeng ; Wang, Yaming ; Huang, Wenqing ; Bao, Xiaomin
Author_Institution :
Coll. of Inf. & Electron., Zhejiang Sci-Tech Univ., Hangzhou, China
Volume :
2
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
630
Lastpage :
634
Abstract :
Human motion tracking is crucial for many important applications. In this paper we propose an approach to human motion tracking from monocular image sequences. First, a system is developed for solving the occlusion problems. The system is based on recursive least square (RLS) and genetic algorithm (GA) that introduced a new way to eliminate occlusion. Then, in order to reduce the noise of position coordinates, the maximum a posteriori (MAP) estimator is jointed into the system. The tracking capability of proposed algorithm is proved. Experimental results on image sequences of different human motion, including walking and running, demonstrate the feasibility of the proposed approach.
Keywords :
feature extraction; genetic algorithms; image motion analysis; image sequences; least squares approximations; maximum likelihood estimation; recursive filters; MAP filter; RLS; feature point tracking; genetic algorithm; human motion tracking; maximum a posteriori estimator; monocular image sequences; occlusion problems; recursive least square; Algorithm design and analysis; Feature extraction; Humans; Image sequences; Noise; Prediction algorithms; Tracking; MAP; RLS; genetic algorithm; motion analysis; tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
Type :
conf
DOI :
10.1109/FSKD.2010.5569439
Filename :
5569439
Link To Document :
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