Computer Vision: Models, Learning, and Inference
by Simon J.D. Prince
Publisher: Cambridge University Press 2012
ISBN/ASIN: 1107011795
ISBN-13: 9781107011793
Number of pages: 665
Description:
This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data.
Download or read it online for free here:
Download link
(105MB, PDF)
Similar books
Recent Advances in Face Recognitionby Kresimir Delac, Mislav Grgic, Marian Stewart Bartlett - IN-TECH
The main ideas in the area of face recognition are security applications and human-computer interaction. The goal of this book is to provide the reader with the most up to date research performed in automatic face recognition.
(10674 views)
Computer Vision: Algorithms and Applicationsby Richard Szeliski - Springer
The book emphasizes basic techniques that work under real-world conditions, not the esoteric mathematics without practical applicability. The text is suitable for a senior-level undergraduates in computer science and electrical engineering.
(27993 views)
Machine Visionby R. Jain, R. Kasturi, B. G. Schunck - McGraw-Hill
The book is intended to provide a balanced introduction to machine vision. Basic concepts are introduced with only essential mathematical elements. The details to allow implementation and use of vision algorithm in practical application are provided.
(19255 views)
Intelligent Vision Systems for Industryby Bruce G. Batchelor - Springer-Verlag
The author introduces the basic concepts of machine vision, then develops these ideas to describe intelligent imaging techniques for use in a new generation of industrial imaging systems. Several case studies in industrial applications are discussed.
(12695 views)