Robust Superpixel Tracking via Depth Fusion | |
Yuan, Yuan![]() | |
作者部门 | 光学影像学习与分析中心 |
2014 | |
发表期刊 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
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ISSN | 1051-8215 |
卷号 | 24期号:1页码:15-26 |
摘要 | Although numerous trackers have been designed to adapt to the nonstationary image streams that change over time, it remains a challenging task to facilitate a tracker to accurately distinguish the target from the background in every frame. This paper proposes a robust superpixel-based tracker via depth fusion, which exploits the adequate structural information and great flexibility of mid-level features captured by superpixels, as well as the depth-map's discriminative ability for the target and background separation. By introducing graph-regularized sparse coding into the appearance model, the local geometrical structure of data is considered, and the resulting appearance model has a more powerful discriminative ability. Meanwhile, the similarity of the target superpixels' neighborhoods in two adjacent frames is also incorporated into the refinement of the target estimation, which helps a more accurate localization. Most importantly, the depth cue is fused into the superpixel-based target estimation so as to tackle the cluttered background with similar appearance to the target. To evaluate the effectiveness of the proposed tracker, four video sequences of different challenging situations are contributed by the authors. The comparison results demonstrate that the proposed tracker has more robust and accurate performance than seven ones representing the state-of-the-art. |
文章类型 | Article |
关键词 | Computer Vision Depth Fusion Graph Regularized Sparse Coding Object Tracking Segmentation Superpixel |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1109/TCSVT.2013.2273631 |
收录类别 | SCI ; EI |
关键词[WOS] | VISUAL TRACKING ; OBJECT TRACKING ; SEGMENTATION ; CONTOUR ; KERNEL ; MODEL |
语种 | 英语 |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Electrical & Electronic |
WOS记录号 | WOS:000329874700002 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/22353 |
专题 | 光谱成像技术研究室 |
作者单位 | 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 |
推荐引用方式 GB/T 7714 | Yuan, Yuan,Fang, Jianwu,Wang, Qi. Robust Superpixel Tracking via Depth Fusion[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2014,24(1):15-26. |
APA | Yuan, Yuan,Fang, Jianwu,&Wang, Qi.(2014).Robust Superpixel Tracking via Depth Fusion.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,24(1),15-26. |
MLA | Yuan, Yuan,et al."Robust Superpixel Tracking via Depth Fusion".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 24.1(2014):15-26. |
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 | ||
Robust Superpixel Tr(15368KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY | 请求全文 |
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