A Compact Optical Flow based Motion Representation for Real time Action Recognition in Surveillance Scenes

CASIA OpenIR > 模式识别实验室

	A Compact Optical Flow based Motion Representation for Real time Action Recognition in Surveillance Scenes
	Shiquan Wang; Kaiqi Huang; Tieniu Tan
	2009
会议名称	International Conference on Image Processing
会议录名称	IEEE International Conference on Image Processing, 2009
页码	1121-1124
会议日期	2009
会议地点	Cairo, Egypt
摘要	We address the problem of action recognition. Our aim is to recognize single person activities in surveillance scenes. To meet the requirements of real scene action recognition, we present a compact motion representation for human activity recognition. With the employment of efficient features extracted from optical flow as the main part, together with global information, our motion representation is compact and discriminative. We also build a novel human action dataset(CASIA) in surveillance scene with three vertically different viewpoints and distant people. Experiments on CASIA dataset and WEIZMANN dataset show that our method can achieve satisfying recognition performance with low computational cost as well as robustness against both horizontal(panning) and vertical(tilting) viewpoint changes.
关键词	Feature Extraction image Motion Analysis surveillance
语种	英语
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12704
专题	模式识别实验室
通讯作者	Kaiqi Huang
作者单位	中国科学院自动化研究所
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Shiquan Wang,Kaiqi Huang,Tieniu Tan. A Compact Optical Flow based Motion Representation for Real time Action Recognition in Surveillance Scenes[C],2009:1121-1124.