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Sparse Representation, Modeling and Learning in Visual Recognition

Theory, Algorithms and Applications

  • Hong┬áCheng

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Introduction and Fundamentals

    1. Front Matter
      Pages 1-1
    2. Hong Cheng
      Pages 3-19
  3. Sparse Representation, Modeling and Learning

    1. Front Matter
      Pages 55-55
    2. Hong Cheng
      Pages 57-90
  4. Visual Recognition Applications

    1. Front Matter
      Pages 153-153
    2. Hong Cheng
      Pages 155-181
    3. Hong Cheng
      Pages 183-200
  5. Advanced Topics

    1. Front Matter
      Pages 213-213
    2. Hong Cheng
      Pages 215-235
  6. Back Matter
    Pages 237-257

About this book

Introduction

This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision.

Topics and features:

  • Provides a thorough introduction to the fundamentals of sparse representation, modeling and learning, and the application of these techniques in visual recognition
  • Describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition
  • Covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers
  • Discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning
  • Includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book

Researchers and graduate students interested in computer vision, pattern recognition and robotics will find this work to be an invaluable introduction to techniques of sparse representations and compressive sensing.

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.

Keywords

Compressed Sensing Dictionary Learning Sparse Bayesian Learning Sparse Coding Sparse Representation Sparsity Induced Similarity Visual Recognition

Authors and affiliations

  • Hong┬áCheng
    • 1
  1. 1.Univ. of Electronic Science & TechnologyChengduChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-6714-3
  • Copyright Information Springer-Verlag London 2015
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-6713-6
  • Online ISBN 978-1-4471-6714-3
  • Series Print ISSN 2191-6586
  • Series Online ISSN 2191-6594
  • Buy this book on publisher's site
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