Object Detection and Recognition in Digital Images: Theory and Practice
| AUTHOR | Cyganek; Cyganek; Cyganek et al. |
| PUBLISHER | Wiley (08/05/2013) |
| PRODUCT TYPE | Hardcover (Hardcover) |
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 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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Product Format
Product Details
ISBN-13:
9780470976371
ISBN-10:
0470976373
Binding:
Hardback or Cased Book (Sewn)
Content Language:
English
More Product Details
Page Count:
560
Carton Quantity:
12
Product Dimensions:
6.70 x 1.20 x 9.90 inches
Weight:
2.20 pound(s)
Feature Codes:
Bibliography,
Index
Country of Origin:
GB
Subject Information
BISAC Categories
Computers | Computer Engineering
Computers | Physics - Crystallography
Dewey Decimal:
621.399
Library of Congress Control Number:
2012050754
Descriptions, Reviews, Etc.
publisher marketing
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.
Show More
List Price $155.95
Your Price
$154.39