Multi-scale spatio-temporal context visual tracking algorithm based on target model adaptive update
文献类型：会议论文
| 作者 | Chen FL(陈法领)1,3,4,5,6 ; Ding QH(丁庆海)1,2; Luo HB(罗海波)1,3,4,6; Hui B(惠斌)1,3,4,6; Chang Z(常铮)1,3,4,6; Liu YP(刘云鹏)1,3,4,6
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| 出版日期 | 2020 |
| 会议日期 | August 25-27, 2020 |
| 会议地点 | Xiamen, China |
| 关键词 | computer vision visual tracking spatio-temporal context target model adaptive update scale estimation |
| 页码 | 1-8 |
| 英文摘要 | It is well known that achieving a robust visual tracking task is quite difficult, since it is easily interfered by scale variation, illumination variation, background clutter, occlusion and so on. Nevertheless, the performance of spatio-temporal context algorithm is remarkable, because the spatial context information of target is effectively employed in this algorithm. However, the capabilities of discriminate target and adjust to scale variation need to promote in complex scene. Furthermore, due to lack of an appropriate target model update strategy, its tracking capability also deteriorates. In the interest of tackling these problems, a multi-scale spatio-temporal context visual tracking algorithm based on target model adaptive update is proposed. Firstly, the histogram of oriented gradient features are adopted to describe the target and its surrounding regions to improve its discriminate ability. Secondly, a multi-scale estimation method is applied to predict the target scale variation. Then, the peak and the average peak to correlation energy of confidence map response are combined to evaluate the visual tracking status. When the status is stable, the current target is expressed in a low rank form and a CUR filter is learned. On the contrary, the CUR filter will be triggered to recapture the target. Finally, the experimental results demonstrate that the robustness of this algorithm is promoted obviously, and its overall performance is better than comparison algorithms. |
| 产权排序 | 1 |
| 会议录 | AOPC 2020: Optical Sensing and Imaging Technology
 |
| 会议录出版者 | SPIE |
| 会议录出版地 | Bellingham, USA |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| ISBN号 | 978-1-5106-3955-3 |
| WOS记录号 | WOS:000651815600017 |
| 源URL | [http://ir.sia.cn/handle/173321/27890]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 通讯作者 | Luo HB(罗海波) |
| 作者单位 | 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China 2.Space Star Technology Co, LTD, Beijing, 100086, China 3.The Key Lab of Image Understanding and Computer Vision, Liaoning Province, Shenyang, 110016, China 4.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, 110016, China 5.University of Chinese Academy of Sciences, Beijing, 100049, China 6.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China |
| 推荐引用方式 GB/T 7714 | Chen FL,Ding QH,Luo HB,et al. Multi-scale spatio-temporal context visual tracking algorithm based on target model adaptive update[C]. 见:. Xiamen, China. August 25-27, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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