Occlusion Detection via Structured Sparse Learning for Robust Object Tracking
Zhang, Tianzhu1; Ghanem, Bernard2; Xu, Changsheng3; Ahuja, Narendra4
2014
发表期刊Advances in Computer Vision and Pattern Recognition
期号71页码:93-112
摘要Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios, these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object’s track. This is the case when significant occlusion occurs. To accommodate for nonsparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our proposed tracker consistently outperforms the state-of-the-art trackers.
关键词Tracking
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20488
专题模式识别国家重点实验室_多媒体计算与图形学
作者单位1.dvanced Digital Sciences Center of Illinois, Singapore, Singapore
2.King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
3.Institute of Automation, Chinese Academy of Sciences, CSIDM, People’s Republic of China
4.University of Illinois at Urbana-Champaign, Urbana, IL, USA
推荐引用方式
GB/T 7714
Zhang, Tianzhu,Ghanem, Bernard,Xu, Changsheng,et al. Occlusion Detection via Structured Sparse Learning for Robust Object Tracking[J]. Advances in Computer Vision and Pattern Recognition,2014(71):93-112.
APA Zhang, Tianzhu,Ghanem, Bernard,Xu, Changsheng,&Ahuja, Narendra.(2014).Occlusion Detection via Structured Sparse Learning for Robust Object Tracking.Advances in Computer Vision and Pattern Recognition(71),93-112.
MLA Zhang, Tianzhu,et al."Occlusion Detection via Structured Sparse Learning for Robust Object Tracking".Advances in Computer Vision and Pattern Recognition .71(2014):93-112.
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