Robust Superpixel Tracking via Depth Fusion

doi:10.1109/TCSVT.2013.2273631

OPT OpenIR > 光谱成像技术研究室

	Robust Superpixel Tracking via Depth Fusion
	Yuan, Yuan; Fang, Jianwu; Wang, Qi
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
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	被引频次：60[WOS] [WOS记录] [WOS相关记录]
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.

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