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Markov Random Field Modeling in Computer Vision

  • Book
  • © 1995

Overview

Authors:
  1. S. Z. Li

    1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

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Part of the book series: Computer Science Workbench (WORKBENCH)

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Table of contents (9 chapters)

  1. Front Matter

    Pages I-XVI
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  2. Introduction

    • S. Z. Li
    Pages 1-35

  3. Low Level MRF Models

    • S. Z. Li
    Pages 37-61

  4. Discontinuities in MRFs

    • S. Z. Li
    Pages 63-81

  5. Discontinuity-Adaptivity Model and Robust Estimation

    • S. Z. Li
    Pages 83-99

  6. High Level MRF Models

    • S. Z. Li
    Pages 101-130

  7. MRF Parameter Estimation

    • S. Z. Li
    Pages 131-156

  8. Parameter Estimation in Optimal Object Recognition

    • S. Z. Li
    Pages 157-184

  9. Minimization — Local Methods

    • S. Z. Li
    Pages 185-206

  10. Minimization — Global Methods

    • S. Z. Li
    Pages 207-230

  11. Back Matter

    Pages 231-264
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Keywords

About this book

Markov random field (MRF) modeling provides a basis for the characterization of contextual constraints on visual interpretation and enables us to develop optimal vision algorithms systematically based on sound principles. This book presents a comprehensive study on using MRFs to solve computer vision problems, covering the following parts essential to the subject: introduction to fundamental theories, formulations of various vision models in the MRF framework, MRF parameter estimation, and optimization algorithms. Various MRF vision models are presented in a unified form, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This book is an excellent reference for researchers working in computer vision, image processing, pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in the subject.

Authors and Affiliations

  • School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

    S. Z. Li

Bibliographic Information

  • Book Title: Markov Random Field Modeling in Computer Vision

  • Authors: S. Z. Li

  • Series Title: Computer Science Workbench

  • DOI: https://doi.org/10.1007/978-4-431-66933-3

  • Publisher: Springer Tokyo

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Japan 1995

  • eBook ISBN: 978-4-431-66933-3Published: 06 December 2012

  • Series ISSN: 1431-1488

  • Edition Number: 1

  • Number of Pages: XVI, 264

  • Number of Illustrations: 120 b/w illustrations

  • Topics: Pattern Recognition, Image Processing and Computer Vision

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