Computer Vision: Principles, Algorithms, Applications, Learning

Previously entitled Computer and Machine Vision, this book clearly and systematically presents the basic methodology of computer vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fifth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date text suitable for undergraduate and graduate students, researchers, and R&D engineers working in this vibrant subject.

See an interview with the author explaining his approach to teaching and learning computer vision - http://scitechconnect.elsevier.com/computer-vision/

New Chapters and Topics

Three new chapters on Machine Learning emphasize the way the subject has been developing; two chapters cover Basic Classification Concepts and Probabilistic Models; and the third covers the principles of Deep Learning Networks and shows their impact on computer vision, reflected in a new chapter Face Detection and Recognition.

A new chapter on Object Segmentation and Shape Models reflects the methodology of machine learning and gives practical demonstrations of its application.

In-Depth Discussions and Applications

Discussions include geometric transformations, the EM algorithm, boosting, semantic segmentation, face frontalisation, RNNs, and other key topics.

Examples and applications—such as the location of biscuits, foreign bodies, faces, eyes, road lanes, surveillance, vehicles, and pedestrians—illustrate the development of real-world vision systems and the realities of practical implementation.

Mathematics, Theory, and Programming

Necessary mathematics and essential theory are made approachable through careful explanations and well-illustrated examples.

The 'recent developments' sections in each chapter aim to keep students and practitioners up to date with this fast-moving subject.

Tailored programming examples—including code, methods, illustrations, tasks, hints, and solutions—mainly involving MATLAB and C++.