Robust visual tracking via consistent low-rank sparse learning

DOI10.1007/S11263-014-0738-0zbMath1398.68605OpenAlexW1977709942MaRDI QIDQ1799927

Bernard Ghanem, Ming-Hsuan Yang, Narendra Ahuja, Tianzhu Zhang, Si Liu

Publication date: 19 October 2018

Published in: International Journal of Computer Vision (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10754/556145

zbMATH Keywords

low-rank representationsparse representationvisual trackingtemporal consistency

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Machine vision and scene understanding (68T45)

Related Items (8)

Visual tracking via subspace learning: a discriminative approach ⋮ Low-rank representation-based object tracking using multitask feature learning with joint sparsity ⋮ Object tracking via dual fuzzy low-rank approximation ⋮ A parallel search strategy based on sparse representation for infrared target tracking ⋮ A multiple template approach for robust tracking of fast motion target ⋮ Robust visual tracking via consistent low-rank sparse learning ⋮ Adaptive channel selection for robust visual object tracking with discriminative correlation filters ⋮ Tensorized multi-view subspace representation learning

Uses Software

• PASCAL VOC
• RASL

Cites Work

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• Robust visual tracking via consistent low-rank sparse learning
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• Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
• Adaptive Appearance Modeling for Video Tracking: Survey and Evaluation
• Learning with Structured Sparsity
• Compressed sensing

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