Object Detection and Recognition in Digital Images: Theory and Practice

  • Publish Date: 2013-08-05
  • Binding: Hardcover
  • Author: Boguslaw Cyganek
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  • Regular price $173.47

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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.


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