A Compact Optical Flow based Motion Representation for Real time Action Recognition in Surveillance Scenes
文献类型：会议论文
| 作者 | Shiquan Wang; Kaiqi Huang ; Tieniu Tan
|
| 出版日期 | 2009 |
| 会议日期 | 2009 |
| 会议地点 | Cairo, Egypt |
| 关键词 | Feature Extraction image Motion Analysis surveillance |
| 页码 | 1121-1124 |
| 英文摘要 | 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. |
| 会议录 | IEEE International Conference on Image Processing, 2009
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12704]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Kaiqi Huang |
| 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]. 见:. Cairo, Egypt. 2009. |
入库方式： OAI收割
来源：自动化研究所
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