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Gait Recognition Method Based on Dynamic Energy Feature |
CHAI YanMei, ZHAO RongChun, TIAN GuangJian, JIA JingPing |
School of Computer, Northwestern Polytechnical University, Xi’an 710072 |
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Abstract Recognizing people by their gait is a recent research hotspot. Compared with other biometrics, gait has the following three advantages: distant recognition, uninvasive and difficult to conceal. A new gait recognition method based on the dynamic energy feature is proposed in this paper. Firstly, the background is initialized automatically in the gait sequence. Then the binary silhouette of a walking person is detected by background subtraction technology. Next, the dynamic energy feature matrixes are extracted from binary silhouette sequences. Finally, the correlation coefficient measure and two different classification methods (NN and KNN) are used to recognize different subjects. Experimental results show that the new method is effective. Recognition rate of over 90% on both UCSD database and CMU database are achieved.
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Received: 22 July 2005
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