| Part-based Online Tracking with Geometry Constraint and Attention Selection | |
Fang, Jianwu1; Wang, Qi2; Yuan, Yuan1
| |
| 作者部门 | 光学影像学习与分析中心 |
| 2014-05-01 | |
| 发表期刊 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
 |
| ISSN | 1051-8215 |
| 卷号 | 24期号:5页码:854-864 |
| 摘要 | Visual tracking in condition of occlusion, appearance or illumination change has been a challenging task over decades. Recently, some online trackers, based on the detection by classification framework, have achieved good performance. However, problems are still embodied in at least one of the three aspects: 1) tracking the target with a single region has poor adaptability for occlusion, appearance or illumination change; 2) lack of sample weight estimation, which may cause overfitting issue; and 3) inadequate motion model to prevent target from drifting. For tackling the above problems, this paper presents the contributions as follows: 1) a novel part-based structure is utilized in the online AdaBoost tracking; 2) attentional sample weighting and selection is tackled by introducing a weight relaxation factor, instead of treating the samples equally as traditional trackers do; and 3) a two-stage motion model, multiple parts constraint, is proposed and incorporated into the part-based structure to ensure a stable tracking. The effectiveness and efficiency of the proposed tracker is validated upon several complex video sequences, compared with seven popular online trackers. The experimental results show that the proposed tracker can achieve increased accuracy with comparable computational cost. |
| 文章类型 | Article |
| 关键词 | Attention Selection Multiple Parts Constraint Object Tracking Online Adaboost (Oab) Relaxation Factor |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1109/TCSVT.2013.2283646 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | REAL-TIME TRACKING ; OBJECT TRACKING ; VISUAL TRACKING ; NONRIGID OBJECT ; ROBUST TRACKING ; MEAN SHIFT ; FEATURES ; COLOR |
| 语种 | 英语 |
| WOS研究方向 | Engineering |
| WOS类目 | Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000336057400012 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/22355 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning, Xian 710119, Shaanxi, Peoples R China 2.Northwestern Polytech Univ, Xian 710072, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fang, Jianwu,Wang, Qi,Yuan, Yuan. Part-based Online Tracking with Geometry Constraint and Attention Selection[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2014,24(5):854-864. |
| APA | Fang, Jianwu,Wang, Qi,&Yuan, Yuan.(2014).Part-based Online Tracking with Geometry Constraint and Attention Selection.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,24(5),854-864. |
| MLA | Fang, Jianwu,et al."Part-based Online Tracking with Geometry Constraint and Attention Selection".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 24.5(2014):854-864. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Part-based Online Tr（13762KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY | 请求全文 | |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
修改评论