Computer Vision

Kundeninformationen

- Three new chapters on Machine Learning emphasise the way the subject has been developing; Two chapters cover Basic Classification Concepts and Probabilistic Models; and the 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 have been included on geometric transformations, the EM algorithm, boosting, semantic segmentation, face frontalisation, RNNs and other key topics. - Examples and applications-including the location of biscuits, foreign bodies, faces, eyes, road lanes, surveillance, vehicles and pedestrians-give the 'ins and outs' of developing real-world vision systems, showing the realities of practical implementation. - Necessary mathematics and essential theory are made approachable by careful explanations and well-illustrated examples. - The 'recent developments' sections included in each chapter aim to bring students and practitioners up to date with this fast-moving subject. - Tailored programming examples-code, methods, illustrations, tasks, hints and solutions (mainly involving MATLAB and C++)