Low-Rank and Sparse Modeling for Visual Analysis

Download or read book Low-Rank and Sparse Modeling for Visual Analysis written by Yun Fu and published by Springer. This book was released on 2014-10-30 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applications.