Optimization for Computer Vision
An Introduction to Core Concepts and Methods
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Beschreibung
Optimization plays an invaluable role in the exciting and rapidly developing field of computer vision, yet this importance is often overlooked in the literature.
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
This easy-to-follow and applications-focused book is an essential resource for researchers and practitioners seeking guidance on implementing specific methods in computer vision.
Marco Alexander Treiber is a software developer at ASM Assembly Systems, Munich, Germany, where he is Technical Lead in Image Processing for the Vision System of SiPlace placement machines, used in SMT assembly. Among his other publications is the successful Springer title An Introduction to Object Recognition.
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.
Presents a comprehensive overview of topics of relevance to computer vision-related optimization Facilitates understanding by focusing on the fundamental concepts, and providing clearly written and easy-to-follow explanations Supplies detailed information on how to implement specific methods, such as pseudocode
Autor*in
Marco Alexander Treiber
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From the reviews:
“The book is loosely structured around the different approaches to optimization within computer vision … . this is an impressive book that will prove useful for post-graduate and advanced undergraduate readers. The constant use of pseudocode and the grounding within applications and examples make this book suitable as both an introduction to the field as well as a reference text. … it is a useful and important work that I will certainly be using in the years to come.” (Harry Strange, Computing Reviews, April, 2014)
“The goal of this book is to provide a practical guide to optimization algorithms that are commonly used in computer vision applications. … the book very well suited for computer-vision practitioners who are interested in identifying the most appropriate algorithms for their optimization problems and in implementing these algorithms. … this book is a nice reference that can be used in combination with the most computer-vision textbooks and papers.” (Laurens van der Maaten, zbMATH, Vol. 1280, 2014)()