Object Detection and Recognition in Digital Images - Theory and Practice (Hardcover, New)

Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: * Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications. * Places an emphasis on tensor and statistical based approaches within object detection and recognition. * Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods. * Contains numerous case study examples of mainly automotive applications. * Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform.

General

Imprint:	John Wiley & Sons
Country of origin:	United States
Release date:	July 2013
First published:	2013
Authors:	B Cyganek
Dimensions:	252 x 175 x 31mm (L x W x T)
Format:	Hardcover
Pages:	548
Edition:	New
ISBN-13:	978-0-470-97637-1
Categories:	Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	0-470-97637-3
Barcode:	9780470976371

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