Scale adaptive part-based tracking method using multiple correlation filters
文献类型：期刊论文
| 作者 | Luo HB(罗海波)1,2,4,5 ; Chang Z(常铮)1,2,4,5; Hui B(惠斌)1,2,4,5; Chen FL(陈法领)1,2,3,4,5; Chen HY(陈宏宇)1,2,3,4,5
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| 刊名 | Optical Engineering
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| 出版日期 | 2019 |
| 卷号 | 58期号:5页码:1-12 |
| 关键词 | target tracking correlation filter scale estimation deformable parts model computer vision |
| ISSN号 | 0091-3286 |
| 产权排序 | 1 |
| 英文摘要 | Visual tracking plays a significant role in computer vision. Although numerous tracking algorithms have shown promising results, target tracking remains a challenging task due to appearance changes caused by deformation, scale variation, and partial occlusion. Part-based methods have great potential in addressing the deformation and partial occlusion issues. Owing to the addition of multiple part trackers, most of these part-based trackers cannot run in real time. Correlation filters have been used in target tracking owing to their high efficiency. However, the correlation filter-based trackers face great problems dealing with occlusion, deformation, and scale variation. To better address the above-mentioned issues, we present a scale adaptive part-based tracking method using multiple correlation filters. Our proposed method utilizes the scale-adaptive tracker for both root and parts. The target location is determined by the responses of root tracker and part trackers collaboratively. To estimate the target scale more precisely, the root scale and each part scale are predicted with the sequential Monte Carlo framework. An adaptive weight joint confidence map is acquired by assigning proper weights to independent confidence maps. Experimental results on the publicly available OTB100 dataset demonstrate that our approach outperforms other state-of-the-art trackers. |
| WOS关键词 | VISUAL TRACKING ; OBJECT TRACKING |
| WOS研究方向 | Optics |
| 语种 | 英语 |
| WOS记录号 | WOS:000481889500017 |
| 源URL | [http://ir.sia.cn/handle/173321/25318]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 通讯作者 | Chen HY(陈宏宇) |
| 作者单位 | 1.Key Lab of Image Understanding and Computer Vision, Liaoning province, Shenyang, China 2.Chinese Academy of Sciences, Key Laboratory of Opto-Electronic Information Processing, Shenyang, China 3.University of Chinese Academy of Sciences, Beijing, China 4.Chinese Academy of Sciences, Institutes for Robotics and Intelligent Manufacturing, Shenyang, China 5.Chinese Academy of Sciences, Shenyang Institute of Automation, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Luo HB,Chang Z,Hui B,et al. Scale adaptive part-based tracking method using multiple correlation filters[J]. Optical Engineering,2019,58(5):1-12. |
| APA | Luo HB,Chang Z,Hui B,Chen FL,&Chen HY.(2019).Scale adaptive part-based tracking method using multiple correlation filters.Optical Engineering,58(5),1-12. |
| MLA | Luo HB,et al."Scale adaptive part-based tracking method using multiple correlation filters".Optical Engineering 58.5(2019):1-12. |
入库方式： OAI收割
来源：沈阳自动化研究所
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