Abstract: Considering clothes and accouterments, gait recognition method based on dynamic feature was proposed in this paper. Firstly, a value could be got by solving the Poisson equation in the gait shape area and a threshold function was constructed for dynamic feature of gait sequence. Secondly, the angle interval mean and variance of all values of the gait silhouette images in a sector region were computed. And the dynamic feature vector was constructed by them. Finally, Support Vector Machine (SVM) was used to classify the gait sequences with clothes and accouterments. The experimental results show the effectiveness of the proposed method in the CASIA gait database.

Key words: gait recognition, Poisson equation, dynamic feature, support vector machine

摘要： 为了在衣着饰物变化条件下进行步态识别，提出了一种基于动态部位特征的步态识别方法。首先，采用泊松方程给步态轮廓内的每个点赋值，并构造合适的阈值函数来提取步态序列的动态部位特征；然后，统计其等角度间隔的扇形区域内的均值和方差，用其构造动态特征向量；最后，利用支持向量机算法在行走人衣着饰物发生变化的条件下进行步态分类。通过在CASIA大规模步态数据库上的实验，验证了该方法的有效性和鲁棒性。

关键词: 步态识别, 泊松方程, 动态特征, 支持向量机