基于空间分布特征的人体动作动态建模识别

摘要

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 linear 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 on the fusion structure of an integrate description by the nearest neighbor classification. Compared to the recognition results of current methods, DMRSD obtains better recognition rate on Weizmann and KTH databases.%　　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。