Rapid and Robust Human Detection and Tracking based on Omega-Shape Features
文献类型：会议论文
| 作者 | Min Li; Zhaoxiang Zhang ; Kaiqi Huang; Tieniu Tan
|
| 出版日期 | 2009-11-07 |
| 会议日期 | 7-10 November 2010 |
| 会议地点 | Cairo, Egypt |
| 关键词 | Robustness Humans Particle Tracking Target Tracking Head Particle Filters Layout Shape Surveillance Image Edge Detection |
| 页码 | 2545-2548 |
| 英文摘要 | This paper proposes a novel method for rapid and robust human detection and tracking based on the omega-shape features of people's head-shoulder parts. There are two modules in this method. In the first module, a Viola-Jones type classifier and a local HOG (Histograms of Oriented Gradients) feature based AdaBoost classifier are combined to detect head-shoulders rapidly and effectively. Then, in the second module, each detected head-shoulder is tracked by a particle filter tracker using local HOG features to model target's appearance, which shows great robustness in scenarios of crowding, background distractors and partial occlusions. Experimental results demonstrate the effectiveness and efficiency of the proposed approach. |
| 会议录 | IEEE International Conference on Image Processing, 2009
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12706]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Min Li |
| 推荐引用方式 GB/T 7714 | Min Li,Zhaoxiang Zhang,Kaiqi Huang,et al. Rapid and Robust Human Detection and Tracking based on Omega-Shape Features[C]. 见:. Cairo, Egypt. 7-10 November 2010. |
入库方式： OAI收割
来源：自动化研究所
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