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Object Recognition
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Object Recognition

Object Recognition

Fundamentals and Case Studies

M. Bennamoun, G.J. Mamic

350 pages, parution le 06/02/2002

Résumé

This volume introduces the fundamental concepts and tools involved in the design and implementation of object recognition systems. Divided into three parts, it first introduces the topic and covers the acquisition of images, then details 3-D object reconstruction, modelling and matching, and finally describes typical recognition systems using case studies. Key features include: Extensive literature surveys of state-of-the-art systems An FTP site from which readers can obtain the MATLAB codes used to generate some of the results found in the text: ftp://ftp.springer.de/pub/cs/object_recognition/ Object Recognition will be essential reading for research scientists, advanced undergraduate and postgraduate students in computer vision, image processing and pattern classification. It will also be of interest to practitioners working in the field of computer vision.

Contents

Part A - Introduction and Acquisition Systems:

1. Introduction.
2. Stereo Matching and Reconstruction of a Depth Map.

Part A - Summary.

Part B - Database Creation and Modeling for 3D Object Recognition:

3. 3-D Object Creation for Recognition.
4. Object Representation and Feature Matching.

Part B - Summary.

Part C - Vision Systems - Case Studies:

5. Optical Character Recognition.
6. Recognition by Parts and Part Segmentation Techniques.
7. 3D Object Recognition Systems.

Part C - Summary:

Appendices

A. Vector and Matrix Analysis.
B. Principal Component Analysis.
C. Optimisation Fundamentals.
D. Differential Geometry - Basic Principles.
E. Spline Theory.
F. Detailed Derivation of Registration Equations.

References.
Index.

Caractéristiques techniques

  PAPIER
Éditeur(s) Springer
Auteur(s) M. Bennamoun, G.J. Mamic
Parution 06/02/2002
Nb. de pages 350
Format 16 x 24
Couverture Broché
Poids 751g
Intérieur Noir et Blanc
EAN13 9781852333980
ISBN13 978-1-85233-398-0

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