Издательство Springer, 2002, -349 pp.This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It represents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acquisition, 3-D object reconstruction, object modelling, and the matching of objects, all of which are essential in the construction of an object recognition system. The book is divided into three parts. Part A provides the reader with an introduction into object recognition and covers the acquisition of images. Part B details the 3-D object reconstruction, modelling and matching, and forms the fulcrum of the manuscript. Finally, Part C describes typical recognition systems using case studies, which illustrates the application of the fundamentals covered in the previous parts. The code used to generate the results that are presented in the case studies may be found at the following FTP site: ftp://ftp.springer.de/pubjcs/object_recognition. The reader is given a road map through all of this literature in the form of a taxonomy that is constructed in the introduction. In addition, each chapter in Parts A and B of the manuscript contains an extensive literature survey of state-of-the-art systems available in specific areas. These surveys are summarised in detailed tables and taxonomies at the beginning of each of the chapters. The book should appeal to both engineers and computer scientists, in particular advanced undergraduate students, postgraduate students and researchers. Hopefully, researchers in other disciplines, such as psychology, will also find the manuscript useful.Part A - Introduction and Acquisition Systems Introduction Stereo Matching and Reconstruction of a Depth Map Part B - Database Creation and Modelling for 3-D Object 3-D Object Creation for Recognition Object Representation and Feature Matching Part C - Vision Systems - Case Studies Optical Character Recognition Recognition by Parts and Part Segmentation Techniques 3-D Object Recognition Systems Appendices A. Vector and Matrix Analysis B. Principal Component Analysis C. Optimisation Fundamentals D. Differential Geometry - Basic Principles E. Spline Theory F. Detailed Derivation of Registration Equations
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