An unsupervised stereo matching cost based on sparse representation

DOI10.1142/S0219691320500605OpenAlexW3085153463MaRDI QIDQ5150118

Chunbo Cheng, Hong Li, Li-Ming Zhang

Publication date: 9 February 2021

Published in: International Journal of Wavelets, Multiresolution and Information Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0219691320500605

zbMATH Keywords

convex quadratic programmingstereo matchingsparse representationinterior point algorithm

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Quadratic programming (90C20) Interior-point methods (90C51) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (1)

Disparity estimation based on fusion of vision and LiDAR

Uses Software

• EdgeStereo

Cites Work

• Unnamed Item
• Interior-point methods
• A taxonomy and evaluation of dense two-frame stereo correspondence algorithms
• Real-time correlation-based stereo vision with reduced border errors
• Efficient image fusion with approximate sparse representation
• Improved combination of RPCA and MEL for sparse representation-based face recognition
• Learning Multiscale Sparse Representations for Image and Video Restoration
• Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Optimization
• A Blind Watermarking Scheme Using New Nontensor Product Wavelet Filter Banks
• Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ ¹ minimization

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