A Statistical Model Based on Spatio-temporal Features for Action Recognition

摘要：

Local spatio-temporal features have recently become a popular video representation for action recognition. In this paper, we propose a statistical model based on sparse representation of space-time features. The Harris3D detector, which extends the Harris detector for images to image sequences, is used as a feature detector, and histograms of gradient orientations (HOG) is used as a feature descriptor. The statistical distribution of the local spatio-temporal features for each action category is obtained using the independent component analysis (ICA). Finally, we test our model on public action database KTH, and the recognition results demonstrate the effectiveness of our model.

关键词： spatio-temporal feature ICA action recognition

作者: Jiangrong Ni Jinhua Xu

作者单位: Department of Computer Science and Technology East China Normal University Shanghai, China

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 1619-1623

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）