Object Detection and Recognition in Digital Images: Theory and Practice
Boguslaw Cyganek(auth.)
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.
Chapter 1 Introduction (pages 1–8):
Chapter 2 Tensor Methods in Computer Vision (pages 9–188):
Chapter 3 Classification Methods and Algorithms (pages 189–345):
Chapter 4 Object Detection and Tracking (pages 346–407):
Chapter 5 Object Recognition (pages 408–486):
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.
Chapter 1 Introduction (pages 1–8):
Chapter 2 Tensor Methods in Computer Vision (pages 9–188):
Chapter 3 Classification Methods and Algorithms (pages 189–345):
Chapter 4 Object Detection and Tracking (pages 346–407):
Chapter 5 Object Recognition (pages 408–486):
Catégories:
Année:
2013
Editeur::
Wiley
Langue:
english
Pages:
555
ISBN 10:
1118618386
ISBN 13:
9781118618387
Fichier:
PDF, 9.79 MB
IPFS:
,
english, 2013
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