Particle filter based multi-pedestrian tracking by HOG and HOF
文献类型：会议论文
| 作者 | Can Yang; Baopu Li; Guoqing Xu |
| 出版日期 | 2014 |
| 会议名称 | 2014 4th IEEE International Conference on Information Science and Technology, ICIST 2014 |
| 会议地点 | Shenzhen, China |
| 英文摘要 | Automatic pedestrian detection and tracking is an important issue in the field of computer vision and robot navigation. We propose a scheme to implement multi-pedestrian tracking in a scene obtained by a static camera. We combine HOG and HOFfeatures to describe the characteristics of persons. AdaBoost algorithm is then utilized to train a strong classifier for better detection accuracy of persons. We use particle filter as the tracking framework and train a online SVM classifier, which is the observation model, by reliable samples from associated detections without occlusion. In consideration of the target's velocity into the weights calculation, the data association is more reliable. The preliminary experiments on some benchmark data demonstrate the feasibility of the proposed scheme. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5577]  |
| 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 | Can Yang,Baopu Li,Guoqing Xu. Particle filter based multi-pedestrian tracking by HOG and HOF[C]. 见:2014 4th IEEE International Conference on Information Science and Technology, ICIST 2014. Shenzhen, China. |
入库方式： OAI收割
来源：深圳先进技术研究院
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