DocumentCode :
2630833
Title :
3-D Human Posture Recognition System Using 2-D Shape Features
Author :
Hu, Jwu-Sheng ; Su, Tzung-Min ; Lin, Pei-Ching
Author_Institution :
Dept. of Electr. & Control Eng., Nat. Chiao Tung Univ., Hsinchu
fYear :
2007
fDate :
10-14 April 2007
Firstpage :
3933
Lastpage :
3938
Abstract :
This paper presents an integrated framework for recognizing 3D human posture from 2D images. A flexible combinational algorithm motivated by the novel view expressed by Cyr and Kimia (2004) is proposed to generate the aspects of 3D human postures as the posture prototype using features extracted from the collected 2D images sampled at random intervals from the viewing sphere. Frequency and phase information of the posture are calculated from the Fourier descriptors (FDs) of the sampled points on the posture contour as the main and assistant features to extract the characteristic views as the aspects. Moreover, a modified particle filter is applied to improve the robustness of human posture recognition for continuous monitoring. Experimental trials on synthetic and real sequences have shown the effectiveness of the proposed method.
Keywords :
Fourier transforms; computer vision; feature extraction; object recognition; particle filtering (numerical methods); pose estimation; stereo image processing; 2D shape features; 3D human posture recognition system; Fourier descriptors; feature extraction; flexible combinational algorithm; particle filter; posture contour; Data mining; Feature extraction; Frequency; Humans; Image recognition; Monitoring; Particle filters; Prototypes; Robustness; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2007 IEEE International Conference on
Conference_Location :
Roma
ISSN :
1050-4729
Print_ISBN :
1-4244-0601-3
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ROBOT.2007.364082
Filename :
4209700
Link To Document :
بازگشت