基于动态能量特征的步态识别方法

Gait Recognition Method Based on Dynamic Energy Feature

步态是生物特征识别领域的一个新兴热点,它有三大优势:远距离识别、非侵犯性和难于隐藏.本文提出一种新的基于动态能量特征的步态识别算法.首先对输入的步态序列进行背景建模;然后分割出图像中运动人体的二值侧影;再从侧影序列中提取出步态的动态能量特征矩阵;最后用标准的模式分类技术对个体的身份做出识别.实验结果表明,该方法不仅简单、易操作,而且在 UCSD 和 CMU 数据集上均获得90%以上的高识别率.

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.