Markov Random Field Modeling in Computer Vision

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Synopsis

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.

Book details

Edition:
1995
Series:
Computer Science Workbench
Author:
S.Z. Li
ISBN:
9784431669333
Related ISBNs:
9784431701453
Publisher:
Springer Japan, Tokyo
Pages:
N/A
Reading age:
Not specified
Includes images:
No
Date of addition:
2022-08-17
Usage restrictions:
Copyright
Copyright date:
1995
Copyright by:
N/A 
Adult content:
No
Language:
English
Categories:
Art and Architecture, Computers and Internet, Nonfiction