Multi-pedestrian Tracking Based on Social Forces
文献类型：会议论文
| 作者 | Jia K(贾凯)1; Di, Pei1; Kang J(康杰)2,3 ; Ren HL(任恒乐)2,3; Xu F(徐方)1; Zou FS(邹风山)1
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| 出版日期 | 2018 |
| 会议日期 | August 24-27, 2018 |
| 会议地点 | Shenyang, China |
| 页码 | 527-532 |
| 英文摘要 | Multi-pedestrian tracking based on video has always faced many problems. Tracking-by-detection paradigm is a popular method to solve these problems. For example, due to the influence of sensors, lighting, background, detection may result in some false detections and missed detections. In order to solve this problem, in this paper, we propose a new tracking method based on the social force model. Here, pedestrians are divided into two categories: candidate pedestrians and real pedestrians. The real pedestrians are the pedestrians we want to track. Both can be transformed into each other by their respective historical records. The social force model is used to predict the position of each person in the next frame, and the weighted distance between the detected pedestrian in the current frame and the detection in the next frame of image is calculated. According to the distance matrix, the Hungarian algorithm is used to assign identities so as to achieve the purpose of multi-pedestrian tracking. Our results were evaluated on the MOT challenges dataset and compared with existing advanced algorithms. The results show that this method outperforms traditional algorithms in the number of mostly tracked (MT), mostly lost (ML) and the number of frames processed per second (FPS). Including Particle filter, traditional social force model and Kalman filter algorithm tracking method. © 2018 IEEE. |
| 产权排序 | 1 |
| 会议录 | 2018 International Conference on Intelligence and Safety for Robotics, ISR 2018
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-5386-5546-7 |
| WOS记录号 | WOS:000455843900092 |
| 源URL | [http://ir.sia.cn/handle/173321/23945]  |
| 专题 | 沈阳自动化研究所_其他 |
| 通讯作者 | Ren HL(任恒乐) |
| 作者单位 | 1.Shenyang SIASUN Robot Automation Co. LTD. China, Shenyang 110168, China 2.University of Chinese Academy of Sciences, Beijing 100049, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Jia K,Di, Pei,Kang J,et al. Multi-pedestrian Tracking Based on Social Forces[C]. 见:. Shenyang, China. August 24-27, 2018. |
入库方式： OAI收割
来源：沈阳自动化研究所
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