Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation

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	Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation
	Hu, Weiming1 ; Li, Wei 1; Zhang, Xiaoqin 1; Maybank, Stephen 2
刊名	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
	2015-04-01
卷号	37 期号:4 页码:816-833
关键词	Visual object tracking tracking multi-objects under occlusions multi-feature joint sparse representation
英文摘要	In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
研究领域[WOS]	Computer Science ; Engineering
关键词[WOS]	VISUAL TRACKING ; ROBUST ; MODELS ; COLOR ; OPTIMIZATION ; RECOGNITION ; CONTEXT ; FILTER
收录类别	SCI
语种	英语
WOS记录号	WOS:000351213400009
公开日期	2015-09-22
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/8089]
专题	自动化研究所_模式识别国家重点实验室_视频内容安全团队
作者单位	1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 2.Univ London Birkbeck Coll, Dept Comp Sci & Informat Syst, London WC1E 7HX, England
推荐引用方式 GB/T 7714	Hu, Weiming,Li, Wei,Zhang, Xiaoqin,et al. Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2015,37(4):816-833.
APA	Hu, Weiming,Li, Wei,Zhang, Xiaoqin,&Maybank, Stephen.(2015).Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,37(4),816-833.
MLA	Hu, Weiming,et al."Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 37.4(2015):816-833.