Low-Rank and Sparse Modeling for Visual Analysis

Fu, Yun

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.

Details

Published by: Springer

Publication Date: 2016-10-01

Format: Paperback

ISBN-13: 9783319355672

DOI: 10.1007/978-3-319-12000-3

Dimensions: 235cm x155cm

Pages: 236