Title :
Based-APF human motion tracking from monocular videos
Author :
Ouyang, Yi ; Ling, Yun ; Xing, Jianguo
Author_Institution :
Coll. of Comput. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou
Abstract :
In this paper, a novel method based on adaptive particle filter (APF) for tracking human motion in monocular videos is proposed. With an initial human skeleton joint point template, we use the probability density propagation of the particle filers through the model. This algorithm can automatically deal with tracking issues such as occlusion and auto-occlusion. Experimental results from 20 classes monocular videos show that the proposed method is robust and that the tracking results are good.
Keywords :
adaptive filters; image motion analysis; learning (artificial intelligence); particle filtering (numerical methods); probability; tracking filters; video signal processing; adaptive particle filter method; human motion model learning tracking; human skeleton joint point template; monocular video; probability density propagation; Biological system modeling; Filtering; Humans; Joints; Motion analysis; Particle filters; Particle tracking; Predictive models; Robustness; Videos; human motion; monocular video; particle filter; video tracking;
Conference_Titel :
Image Analysis and Signal Processing, 2009. IASP 2009. International Conference on
Conference_Location :
Taizhou
Print_ISBN :
978-1-4244-3987-4
DOI :
10.1109/IASP.2009.5054581
