Title :
Incomplete motion feature tracking algorithm in video sequences
Author :
Luo, Zhongxiang ; Zhuang, Yueting ; Liu, Feng ; Pan, Yunhe
Author_Institution :
Coll. of Comput. Sci. & Eng., Zhejiang Univ., Hangzhou, China
Abstract :
To effectively track incomplete motion features, a novel feature tracking algorithm for motion capture is presented. According to feature attributes and relationship among features, extracted features are classified as four types of features. Then different strategies are applied to track different kinds of features. To verify the tracks, cross correlation test and predicted 3D model based test are used to test and remove outliers. Experimental results demonstrate the effectiveness of our algorithm.
Keywords :
correlation methods; feature extraction; image classification; image motion analysis; prediction theory; tracking; video signal processing; cross correlation; feature extraction; features classification; human models; human motion tracking; incomplete motion feature tracking algorithm; motion capture; outliers removal; predicted 3D model based test; video sequences; Biological system modeling; Brightness; Clustering algorithms; Feature extraction; Humans; Joints; Motion analysis; Predictive models; Tracking; Video sequences;
Conference_Titel :
Image Processing. 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7622-6
DOI :
10.1109/ICIP.2002.1039046