Title :
Gait recognition based on various viewing angles
Author_Institution :
Dept. of Comput. Sci. & Technol., Yanbian Univ., Yanji, China
Abstract :
A method for analyzing and recognizing person gait based on various viewing angles was proposed. Firstly, motion human body was detected by using adaptive background updating algorithm. Then, motion track period, which has been briefed as centroid, was extracted by using 4-directions chain code. Finally, by different trained periods to get corresponding fuzzy sets, and in addition with membership function, three gait types such as jogging, walking and running was recognized. Experimental results show that the method is performed well at moving speed estimation and gait recognition, and it is remarkable robustness for background noise and varying viewing angles.
Keywords :
feature extraction; fuzzy set theory; motion estimation; object detection; object recognition; video signal processing; 4-directions chain code; adaptive background updating algorithm; background noise robustness; fuzzy sets; human body motion detection; membership function; motion track period extraction; moving speed estimation; person gait recognition; varying viewing angle robustness; gait recognition; membership function; motion human body detection; motion speed estimation;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
DOI :
10.1109/ICCSNT.2012.6525954
