摘要
提出了一种基于多区域分割的步态表示方法,将视频中的目标人体区域部分按人体结构特点划分为多个子区,每个子区通过连接人体重心的椭圆进行拟和,建立多连接椭圆的人体结构模型,预处理阶段引入一个归一化过程以实现对各种视角下的步态序列进行表示.识别过程将模型参数作为步态特征,并引入了一定的融合机制对特征进行选择和融合.实验表明,该算法对于多个视角下的步态序列均具有较好的识别性能.
Gait, which has been developed to recognize people by their habitual walking styles, has attracted much attention in recent years. A new method of gait representation is put forward in the paper. In the pretreatment, image processing and computer vision techniques are employed to track and separate objects from the background. By means of dividing human body area in a video sequence into several sub-areas, representing each sub-area through an ellipse whose parameters can be calculated from the corresponding sub-area, a new body structure model called multi-linked ellipse model is established. In order to enable the method to represent gait of various viewing angles other than just single viewing angle, a normalization process is introduced. In the recognition stage, parameters of the model are used as gait signatures and an information fusion algorithm is proposed to select and combine these signatures. Experimental results prove the higher performance of the method.
出处
《计算机学报》
EI
CSCD
北大核心
2006年第10期1876-1881,共6页
Chinese Journal of Computers
基金
国家自然科学基金和山东省科技发展计算项目基金(2005G4201010)资助
关键词
生物特征
步态表示
步态识别
特征提取
信息融合
biometrics
gait expression
gait recognition
feature extraction
information fusion