Introductory Techniques for 3-D Computer Vision / Edition 1

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More About This Textbook

Overview

An applied introduction to modern computer vision, focusing on a set of computational techniques for 3-D imaging, this book covers a wide range of fundamental problems encountered within computer vision and provides detailed algorithmic and theoretical solutions for each. Each chapter concentrates on a specific problem and solves it by building on previous results.

FEATURES:

  • Provides a guide to well-tested theory and algorithms including solutions of problems encountered in modern computer vision.
  • Contains many practical hints highlighted in the book.
  • Develops two parallel tracks in the presentation, showing how fundamental problems are solved using both intensity and range images, the most popular types of images used today.
  • Each chapter contains notes on the literature, review questions, numerical exercises, and projects.
  • Provides an Internet list for accessing links to test images, demos, archives and additional learning material.
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Product Details

  • ISBN-13: 9780132611084
  • Publisher: Prentice Hall
  • Publication date: 3/6/1998
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 343
  • Product dimensions: 7.02 (w) x 9.09 (h) x 0.79 (d)

Table of Contents

Foreword
Preface: About this Book
1 Introduction 1
2 Digital Snapshots 15
3 Dealing with Image Noise 51
4 Image Features 67
5 More Image Features 95
6 Camera Calibration 123
7 Stereopsis 139
8 Motion 177
9 Shape from Single-image Cues 219
10 Recognition 247
11 Locating Objects in Space 279
App. A.1 Experiments: Good Practice Hints 307
App. A.2 Numerical Differentiation 311
App. A.3 The Sampling Theorem 314
App. A.4 Projective Geometry 316
App. A.5 Differential Geometry 320
App. A.6 Singular Value Decomposition 322
App. A.7 Robust Estimators and Model Fitting 326
App. A.8 Kalman Filtering 328
App. A.9 Three-dimensional Rotations 332
Index 335
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