Optimization for Computer Vision: An Introduction to Core Concepts and Methods

✍ Scribed by Marco Alexander Treiber

• Publisher: Springer
• Year: 2013
• Tongue: English
• Leaves: 266
• Series: Advances in Computer Vision and Pattern Recognition
• Edition: 1
• Category: Library

✦ Synopsis

This practical and authoritative text/reference presents a broad introduction to the optimization methods used specifically in computer vision. In order to facilitate understanding, the presentation of the methods is supplemented by simple flow charts, followed by pseudocode implementations that reveal deeper insights into their mode of operation. These discussions are further supported by examples taken from important applications in computer vision. Topics and features: provides a comprehensive overview of computer vision-related optimization; covers a range of techniques from classical iterative multidimensional optimization to cutting-edge topics of graph cuts and GPU-suited total variation-based optimization; describes in detail the optimization methods employed in computer vision applications; illuminates key concepts with clearly written and step-by-step explanations; presents detailed information on implementation, including pseudocode for most methods.

✦ Table of Contents

Front Matter....Pages i-xi
Introduction....Pages 1-16
Continuous Optimization....Pages 17-65
Linear Programming and the Simplex Method....Pages 67-85
Variational Methods....Pages 87-128
Correspondence Problems....Pages 129-175
Graph Cuts....Pages 177-220
Dynamic Programming (DP)....Pages 221-254
Back Matter....Pages 255-257

✦ Subjects

Image Processing and Computer Vision; Optimization