基于空间分布特征的人体动作动态建模识别  

Human Action Dynamic Modeling Recognition Based on Spatial Distribution Feature

作　　者：蔺广逢[1] 朱虹[2] 范彩霞[1] 张二虎[1] 

机构地区：[1]西安理工大学信息科学系西安710048 [2]西安理工大学自动化与信息工程学院西安710048

出　　处：《模式识别与人工智能》2013年第3期293-299,共7页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.61073092);国家国际科技合作专项基金项目(No.2011DFR10480)资助

摘　　要：人体动作的表面特征和动态特征无统一性描述,导致无法精确地区分人体动作.文中提出基于空间分布特征的人体动作动态建模识别方法(DMRSD).利用相对极坐标划分特征的空间区域,统计局部区域非零信息点数目,形成空间分布特征描述表面特征.然后利用自回归滑动平均动态模型建模空间特征序列,形成模型参数特征描述动态时间结构特征.最后通过各参数特征的相似矩阵线性关系假设,结构融合表面特征和动态运动特征,形成统一性描述特征.用最近邻识别人体动作.在Weizmann和KTH库中比对当前方法的识别结果,文中方法获得较好的识别性能.The appearance feature and dynamic feature of human action have not an integrate description, which leads to distinguish human action inaccurately. In this paper, human action dynamic modeling recognition based on the spatial distribution feature （DMRSD） is proposed. Firstly, the spatial region of the feature is divided into a number of local regions by the relative polar coordinates, the statistic number of the nonzero information points is obtained in these local regions, and these numbers form a spatial distribution feature which describes the action appearance feature. Then, these spatial distribution feature sequences are modeled by autoregressive moving average model, then the feature of model parameter is obtained, which represents the dynamic time structure. Finally, the hnear relation of the affinity matrix of these parameter features is hypothesized, the appearance feature structure and the dynamic motion feature structure are fused, and an integrate description is generated. Human action recognition is directly performed Compared Weizmann on the fusion structure of an integrate description by the nearest neighbor classification. to the recognition results of current methods, DMRSD obtains better recognition rate on and KTH databases.

关 键 词：空间分布特征 表面特征 动态特征 自回归滑动平均动态模型 结构融合 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]