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Object Recognition

Fundamentals and Case Studies

  • Book
  • © 2002

Overview

Authors:
  1. M. Bennamoun

    1. Space Centre for Satellite Navigation, School of Electrical and Electronic Systems Engineering, Queensland University of Technology, Brisbane, Australia

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    You can also search for this author in PubMed   Google Scholar

  2. G. J. Mamic

    1. Space Centre for Satellite Navigation, School of Electrical and Electronic Systems Engineering, Queensland University of Technology, Brisbane, Australia

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • The only book to consolidate concepts and tools to design and implement an object recognition system
  • Accompanied by a webpage and ftp site from where readers can download codes from each chapter

Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xiii
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  2. Introduction and Acquisition Systems

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • M. Bennamoun, G. J. Mamic
      Pages 3-28

    3. Stereo Matching and Reconstruction of a Depth Map

      • M. Bennamoun, G. J. Mamic
      Pages 29-96

  3. Database Creation and Modelling for 3-D Object Recognition

    1. Front Matter

      Pages 99-99
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    2. 3-D Object Creation for Recognition

      • M. Bennamoun, G. J. Mamic
      Pages 101-159

    3. Object Representation and Feature Matching

      • M. Bennamoun, G. J. Mamic
      Pages 161-194

  4. Vision Systems — Case Studies

    1. Front Matter

      Pages 197-197
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    2. Optical Character Recognition

      • M. Bennamoun, G. J. Mamic
      Pages 199-220

    3. Recognition by Parts and Part Segmentation Techniques

      • M. Bennamoun, G. J. Mamic
      Pages 221-259

    4. 3-D Object Recognition Systems

      • M. Bennamoun, G. J. Mamic
      Pages 261-293

  5. Back Matter

    Pages 297-350
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Keywords

About this book

Automatie object recognition is a multidisciplinary research area using con­ cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre­ sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui­ sition, 3-D object reconstruction, object modelling, and the matching of ob­ jects, all of which are essential in the construction of an object recognition system.

Authors and Affiliations

  • Space Centre for Satellite Navigation, School of Electrical and Electronic Systems Engineering, Queensland University of Technology, Brisbane, Australia

    M. Bennamoun, G. J. Mamic

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