An Improved Diffusion Maps Method for Action Recognition Using Global and Local Constraints

摘要：

Action recognition is an important research issue in intelligent surveillance and many other automatic video systems. In this paper, we describe a novel method for the human action recognition from its silhouette in the video. In the algorithm, diffusion maps is used for dimensionality reduction as well as to preserve much of the geometrical structure. A global geometry and local temporal similarity is proposed to recognize the feature trajectory of actions in the learned eigen-space. The classification is performed in K-nearest neighbor framework. Extensive experiments on various scenarios from open databases are presented to demonstrate its high performance and strong robustness in comparison with previous algorithms.

关键词： Action recognition diffusion maps Rtransform global similarity local temporal similarity

作者: Feng Zheng Zhan Song

作者单位: Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,China The Chinese University of Hong Kong,Hong Kong,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）