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|2 23
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|a Lin, Zhouchen,
|e author.
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1 |
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|a Low-rank models in visual analysis :
|b theories, algorithms, and applications /
|c Zhouchen Lin, Hongyang Zhang.
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|a London :
|b Academic Press, an imprint of Elsevier,
|c [2017]
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264 |
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|c �2017
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300 |
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|a 1 online resource
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|a text
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|a computer
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|a online resource
|b cr
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1 |
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|a Computer vision and pattern recognition series
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|a Includes bibliographical references and index.
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|a Vendor-supplied metadata.
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|a Front Cover; Low-Rank Models in Visual Analysis; Copyright; Contents; About the Authors; Preface; Acknowledgment; Notations; 1 Introduction; References; 2 Linear Models; 2.1 Single Subspace Models; 2.2 Multi-Subspace Models; 2.3 Theoretical Analysis; 2.3.1 Exact Recovery; 2.3.1.1 Incoherence Conditions; 2.3.1.2 Exact Recoverability of MC; 2.3.1.3 Exact Recoverability of RPCA; 2.3.1.4 Exact Recoverability of RPCA with Missing Values; 2.3.1.5 Exact Recoverability of Outlier Pursuit; 2.3.1.6 Exact Recoverability of Outlier Pursuit with Missing Values; 2.3.1.7 Exact Recoverability of LRR
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|a 2.3.1.8 Exact Recoverability of Robust LRR and Robust Latent LRR2.3.2 Closed-Form Solutions; 2.3.3 Block-Diagonal Structure; References; 3 Nonlinear Models; 3.1 Kernel Methods; 3.2 Laplacian Based Methods; 3.3 Locally Linear Representation; 3.4 Transformation Invariant Clustering; References; 4 Optimization Algorithms; 4.1 Convex Algorithms; 4.1.1 Accelerated Proximal Gradient; 4.1.2 Frank-Wolfe Algorithm; 4.1.3 Alternating Direction Method; 4.1.3.1 Applying ADM to RPCA; 4.1.3.2 Experiments; 4.1.4 Linearized Alternating Direction Method with Adaptive Penalty; 4.1.4.1 Convergence Analysis
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|a 4.1.4.2 Applying LADMAP to LRR4.1.4.3 Experiments; 4.1.5 (Proximal) Linearized Alternating Direction Method with Parallel Splitting and Adaptive Penalty; 4.2 Nonconvex Algorithms; 4.2.1 Generalized Singular Value Thresholding; 4.2.2 Iteratively Reweighted Nuclear Norm Algorithm; 4.2.2.1 Convergence Analysis; 4.2.3 Truncated Nuclear Norm Minimization; 4.2.4 Iteratively Reweighted Least Squares; 4.2.4.1 Convergence Analysis; 4.2.4.2 Experiments; 4.2.5 Factorization Method; 4.3 Randomized Algorithms; 4.3.1 l1 Filtering Algorithm; Recovery of a Seed Matrix; l1 Filtering
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|a 4.3.1.1 Complexity Analysis4.3.1.2 Experiments; 4.3.2 l2,1 Filtering Algorithm; Recovery of a Seed Matrix; l2,1 Filtering; 4.3.2.1 Theoretical Analysis; 4.3.2.2 Complexity Analysis; 4.3.2.3 Experiments; 4.3.3 Randomized Algorithm for Relaxed Robust LRR; 4.3.3.1 Complexity Analysis; 4.3.3.2 Experiments; 4.3.4 Randomized Algorithm for Online Matrix Completion; References; 5 Representative Applications; 5.1 Video Denoising [19]; 5.1.1 Implementation Details; Patch Matching with Outlier Removal; Denoising Patch Matrix; From Denoised Patch to Denoised Image/Video; 5.1.2 Experiments
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|a 5.2 Background Modeling [2]5.2.1 Implementation Details; 5.2.2 Experiments; 5.3 Robust Alignment by Sparse and Low-Rank (RASL) Decomposition [42]; 5.3.1 Implementation Details; 5.3.2 Experiments; 5.4 Transform Invariant Low-Rank Textures (TILT) [58]; 5.5 Motion and Image Segmentation [30,29,4]; Single-Feature Case; Multi-Feature Case; 5.6 Image Saliency Detection [21]; Single-Feature Case; Multiple-Feature Case; 5.7 Partial-Duplicate Image Search [54]; 5.7.1 Implementation Details; Modeling Global Geometric Consistency with a Low-Rank Matrix; Modeling False Matches with a Sparse Matrix
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650 |
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|a Computer vision.
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650 |
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|a Pattern recognition systems.
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650 |
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|a Computer algorithms.
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650 |
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0 |
|a Algorithms.
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650 |
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6 |
|a Vision par ordinateur.
|0 (CaQQLa)201-0074889
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650 |
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|a Reconnaissance des formes (Informatique)
|0 (CaQQLa)201-0028094
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|a Algorithmes.
|0 (CaQQLa)201-0001230
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|a algorithms.
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|a Computer algorithms
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|a Computer vision
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|a Pattern recognition systems
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|0 (OCoLC)fst01055266
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700 |
1 |
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|a Zhang, Hongyang,
|e author.
|
776 |
0 |
8 |
|i Print version:
|a Lin, Zhouchen.
|t Low-rank models in visual analysis.
|d London : Academic Press, an imprint of Elsevier, [2017]
|z 0128127317
|z 9780128127315
|w (OCoLC)981968659
|
830 |
|
0 |
|a Computer vision and pattern recognition series.
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856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128127315
|z Texto completo
|