Human Activity Recognition Based on Improved Diamond Search Block-matching Method

摘要：

A novel method to recognize human activities based on videos is proposed in this paper. These videos are captured by a camera mounted to a human body. We can estimate the activity from the changes of scenes in videos. In this paper, we use the improved diamond search block-matching method to calculate the motion vector. Then we extract key information from the motion vector filed, and design a feature descriptor to describe the motion in frames in a video which can distinguish different motions. After getting feature descriptors, we use SVM classifier to classify different motions with a machine learning method. Experimental results show that our method successfully identifies simple motion such as walking, running, going upstairs and going downstairs. And the block size and the frequency of videos have impacts on classification precision.

关键词： human activity recognition diamond search SVM block-matching

作者: Wenjuan Qi Bo Yin Jiaojiao Wu

作者单位: College of Information Science and Engineering Ocean University of China Qingdao, China

会议类型: 国际会议

会议名称: 2011 Fourth International Symposium on Computational Interlligence and Design 第四届计算智能与设计国际会议 ISCID 2011

会议地点: 杭州

会议语种:英文

页码: 236-239

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）