Title :
Gait Extraction and Recognition Based on Lower Leg and Ankle
Author :
Li, Yi-Bo ; Yang, Qin
Author_Institution :
Shenyang Inst. of Aeronaut. Eng., Shenyang, China
Abstract :
This paper presents gait extraction and recognition method based on a regional information of the lower leg and ankle. First, according to the knowledge of human anatomy, extract lower leg and foot area where the contours of R3, and thin this region. Then the position of ankle is the intersection curve of lower leg and foot, and use least-square method to fit angle sequence of lower leg, and normalize these information and use Discrete Cosine Transform to transform the amplitude Angle sequences. Match two kinds of optimal characteristic, and process result by using feature fusion strategies. The results that experiment in the NLPR gait database show: the lower leg and ankle is significant and effective in the gait feature.
Keywords :
discrete cosine transforms; feature extraction; gait analysis; least squares approximations; NLPR gait database; amplitude angle sequence; ankle; discrete cosine transform; feature fusion; gait extraction; gait feature; gait recognition; intersection curve; least square method; lower leg; Data mining; Discrete cosine transforms; Discrete transforms; Feature extraction; Foot; Footwear; Humans; Image analysis; Image sequences; Leg; ankle; calf; feature fusion; gait recognition; skeleton model;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.714