Condensation-based multi-person detection and tracking with HOG and LBP
文献类型：会议论文
| 作者 | Baopu Li; Can Yang; Qi Zhang; Guoqing Xu |
| 出版日期 | 2014 |
| 会议名称 | 2014 IEEE International Conference on Information and Automation, ICIA 2014 |
| 会议地点 | Hailar, Hulunbuir, China |
| 英文摘要 | Multi-person tracking and detection is widely used in human robot interaction, which has been a hot topic in computer vision. In this paper, we utilize a tracking-by-detection framework to track many persons at the same time. We use HOG and LBP features to describe person's characteristics in a scene and train a strong classifier using Adaboost algorithm. In the tracking part, we use a particle filter to estimate the targets' position. Besides, we train an on-line SVM classifier to improve the accuracy of the tracking results by learning and updating the detector's results. The particles' velocity is also utilized to improve the accuracy of the data association, which relates the detector's output to the tracker's results. Our method is validated feasible on UBC-Hockey benchmark datasets. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5575]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2014 |
| 推荐引用方式 GB/T 7714 | Baopu Li,Can Yang,Qi Zhang,et al. Condensation-based multi-person detection and tracking with HOG and LBP[C]. 见:2014 IEEE International Conference on Information and Automation, ICIA 2014. Hailar, Hulunbuir, China. |
入库方式： OAI收割
来源：深圳先进技术研究院
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