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Object Detection and Recognition in Digital Images ( danke )

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Book Description:
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 kmeans 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.

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