Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications

Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications

by Hong Cheng

Paperback(Softcover reprint of the original 1st ed. 2015)

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Product Details

ISBN-13: 9781447172512
Publisher: Springer London
Publication date: 11/18/2016
Series: Advances in Computer Vision and Pattern Recognition
Edition description: Softcover reprint of the original 1st ed. 2015
Pages: 257
Product dimensions: 6.10(w) x 9.25(h) x 0.02(d)

About the Author

Dr. Hong Cheng is Professor in the School of Automation Engineering, and Deputy Executive Director of the Center for Robotics at the University of Electronic Science and Technology of China. His other publications include the Springer book Autonomous Intelligent Vehicles.

Table of Contents

Part I: Introduction and Fundamentals

Introduction

The Fundamentals of Compressed Sensing

Part II: Sparse Representation, Modeling and Learning

Sparse Recovery Approaches

Robust Sparse Representation, Modeling and Learning

Efficient Sparse Representation and Modeling

Part III: Visual Recognition Applications

Feature Representation and Learning

Sparsity Induced Similarity

Sparse Representation and Learning Based Classifiers

Part IV: Advanced Topics

Beyond Sparsity

Appendix A: Mathematics

Appendix B: Computer Programming Resources for Sparse Recovery Approaches

Appendix C: The source Code of Sparsity Induced Similarity

Appendix D: Derivations

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