Knowledge Commons of Institute of Automation,CAS
Global Coupled Learning and Local Consistencies Ensuring for sparse-based tracking | |
Yang, Yehui1; Xie, Yuan1; Zhang, Wensheng1; Hu, Wenrui1; Tan, Yuanhua2 | |
发表期刊 | NEUROCOMPUTING |
2015-07-21 | |
卷号 | 2015期号:160页码:191-205 |
文章类型 | Article |
摘要 | This paper presents a robust tracking algorithm by sparsely representing the object at both global and local levels. Accordingly, the algorithm is constructed by two complementary parts: Global Coupled Learning (GCL) part and Local Consistencies Ensuring (LCE) part. The global part is a discriminative model which aims to utilize the holistic features of the object via an over-complete global dictionary and classifier, and the dictionary and classifier are coupled learning to construct an adaptive GCL part. While in LCE part, we explore the object's local features by sparsely coding the object patches via a local dictionary, then both temporal and spatial consistencies of the local patches are ensured to refine the tracking results. Moreover, the GCL and LCE parts are integrated into a Bayesian framework for constructing the final tracker. Experiments on fifteen benchmark challenging sequences demonstrate that the proposed algorithm has more effectiveness and robustness than the alternative ten state-of-the-art trackers. (C) 2015 Elsevier B.V. All rights reserved. |
关键词 | Visual Tracking Sparse Representation Dictionary Learning Coupled Learning Consistency Ensuring |
WOS标题词 | Science & Technology ; Technology |
关键词[WOS] | ROBUST VISUAL TRACKING ; APPEARANCE MODEL ; OBJECT TRACKING ; REPRESENTATION ; REGRESSION |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000354139100017 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/8073 |
专题 | 多模态人工智能系统全国重点实验室_人工智能与机器学习(杨雪冰)-技术团队 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Karamay Hongyou Software CO LTD, Karamay 834000, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yang, Yehui,Xie, Yuan,Zhang, Wensheng,et al. Global Coupled Learning and Local Consistencies Ensuring for sparse-based tracking[J]. NEUROCOMPUTING,2015,2015(160):191-205. |
APA | Yang, Yehui,Xie, Yuan,Zhang, Wensheng,Hu, Wenrui,&Tan, Yuanhua.(2015).Global Coupled Learning and Local Consistencies Ensuring for sparse-based tracking.NEUROCOMPUTING,2015(160),191-205. |
MLA | Yang, Yehui,et al."Global Coupled Learning and Local Consistencies Ensuring for sparse-based tracking".NEUROCOMPUTING 2015.160(2015):191-205. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Global Coupled Learn(16651KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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