BN.com Gift Guide

Template Matching Techniques in Computer Vision: Theory and Practice / Edition 1

Hardcover (Print)
Buy New
Buy New from BN.com
$116.95
Used and New from Other Sellers
Used and New from Other Sellers
from $107.84
Usually ships in 1-2 business days
(Save 22%)
Other sellers (Hardcover)
  • All (5) from $107.84   
  • New (4) from $107.84   
  • Used (1) from $116.94   

Overview

The detection and recognition of objects in images is a key research topic in the computer vision community.  Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli:

  • examines the basics of digital image formation, highlighting points critical to the task of template matching;
  • presents basic and  advanced template matching techniques, targeting grey-level images, shapes and point sets;
  • discusses recent pattern classification paradigms from a template matching perspective;
  • illustrates the development of a real face recognition system;
  • explores the use of advanced computer graphics techniques in the development of computer vision algorithms.

Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.

Read More Show Less

Product Details

  • ISBN-13: 9780470517062
  • Publisher: Wiley
  • Publication date: 5/11/2009
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 348
  • Product dimensions: 6.80 (w) x 9.80 (h) x 1.00 (d)

Table of Contents

Preface.

1 Introduction.

1.1 Template Matching and Computer Vision.

1.2 The Book.

1.3 Bibliographical Remarks.

References.

2 The Imaging Process.

2.1 Image Creation.

2.1.1 Light.

2.1.2 Gathering Light.

2.1.3 Diffraction-limited Systems.

2.1.4 Quantum Noise.

2.2 Biological Eyes.

2.2.1 The Human Eye.

2.2.2 Alternative Designs.

2.3 Digital Eyes.

2.4 Digital Image Representations.

2.4.1 TheSampling Theorem.

2.4.2 Image Resampling.

2.4.3 Log-polar Mapping.

2.5 Bibliographical Remarks.

References.

3 Template Matching as Testing.

3.1 Detectionand Estimation.

3.2 Hypothesis Testing.

3.2.1 The Bayes RiskCriterion.

3.2.2 The Neyman–Pearson Criterion.

3.3 An Important Example.

3.4 A Signal Processing Perspective: Matched Filters.

3.5 Pattern Variability and the Normalized Correlation Coefficient.

3.6 Estimation.

3.6.1 Maximum Likelihood Estimation.

3.6.2 Bayes Estimation.

3.6.3 James–Stein Estimation.

3.7 Bibliographical Remarks.

References.

4 Robust Similarity Estimators.

4.1 Robustness Measures.

4.2 M-estimators.

4.3 L1 Similarity Measures.

4.4 Robust Estimation of Covariance Matrices.

4.5 Bibliographical Remarks.

References.

5 Ordinal Matching Measures.

5.1 Ordinal Correlation Measures.

5.1.1 Spearman Rank Correlation.

5.1.2 Kendall Correlation.

5.1.3 Bhat–Nayar Correlation.

5.2 Non-parametric Local Transforms.

5.2.1 The Census and Rank Transforms.

5.2.2 Incremental Sign Correlation.

5.3 Bibliographical Remarks.

References.

6 Matching Variable Patterns.

6.1 Multiclass Synthetic Discriminant Functions.

6.2 Advanced Synthetic Discriminant Functions.

6.3 Non-orthogonal Image Expansion.

6.4 Bibliographical Remarks.

References.

7 Matching Linear Structure: The Hough Transform.

7.1 Getting Shapes: Edge Detection.

7.2 The Radon Transform.

7.3 The Hough Transform: Line and Circle Detection.

7.4 The Generalized Hough Transform.

7.5 Bibliographical Remarks.

References.

8 Low-dimensionality Representations and Matching.

8.1 Principal Components.

8.1.1 Probabilistic PCA.

8.1.2 How Many Components?

8.2 ANonlinear Approach: Kernel PCA.

8.3 Independent Components.

8.4 Linear Discriminant Analysis.

8.4.1 Bayesian Dual Spaces.

8.5 A Sample Application: Photographic-quality Facial Composites.

8.6 Bibliographical Remarks.

References.

9 Deformable Templates.

9.1 A Dynamic Perspective on the Hough Transform.

9.2 Deformable Templates.

9.3 Active Shape Models.

9.4 DiffeomorphicMatching.

9.5 Bibliographical Remarks.

References.

10 Computational Aspects of Template Matching.

10.1 Speed.

10.1.1 Early Jump-out.

10.1.2 TheUse of SumTables.

10.1.3 Hierarchical Template Matching.

10.1.4 Metric Inequalities.

10.1.5 The FFT Advantage.

10.1.6 PCA-basedSpeed-up.

10.1.7 A Combined Approach.

10.2 Precision.

10.2.1 A Perturbative Approach.

10.2.2 Phase Correlation.

10.3 Bibliographical Remarks.

References.

11 Matching Point Sets: The Hausdorff Distance.

11.1 Metric Pattern Spaces.

11.2 Hausdorff Matching.

11.3 Efficient Computation of the Hausdorff Distance.

11.4 Partial Hausdorff Matching.

11.5 Robustness Aspects.

11.6 A Probabilistic Perspective.

11.7 Invariant Moments.

11.8 Bibliographical Remarks.

References.

12 Support Vector Machines and Regularization Networks.

12.1 Learning and Regularization.

12.2 RBF Networks.

12.2.1 RBF Networks for Gender Recognition.

12.3 Support Vector Machines.

12.3.1 Improving Efficiency.

12.3.2 Multiclass SVMs.

12.3.3 Best Practice.

12.4 Bibliographical Remarks.

References.

13 Feature Templates.

13.1 Detecting Templates by Features.

13.2 Parametric FeatureManifolds.

13.3 Multiclass Pattern Rejection.

13.4 Template Features.

13.5 Bibliographical Remarks.

References.

14 Building a Multibiometric System.

14.1 Systems.

14.2 The Electronic Librarian.

14.3 Score Integration.

14.4 Rejection.

14.5 Bibliographical Remarks.

References.

Appendices.

A AnImAl: A Software Environment for Fast Prototyping.

A.1 AnImAl: An Image Algebra.

A.2 Image Representationand Processing Abstractions.

A.3 The AnImAl Environment.

A.4 Bibliographical Remarks.

References.

B Synthetic Oracles for Algorithm Development.

B.1 Computer Graphics.

B.2 Describing Reality: Flexible Rendering Languages.

B.3 Bibliographical Remarks.

References.

C On Evaluation.

C.1 A Note on Performance Evaluation.

C.2 Traininga Classifier.

C.3 Analyzing the Performance of a Classifier.

C.4 Evaluating a Technology.

C.5 Bibliographical Remarks.

References.

Index.

Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star

(0)

4 Star

(0)

3 Star

(0)

2 Star

(0)

1 Star

(0)

Your Rating:

Your Name: Create a Pen Name or

Barnes & Noble.com Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & Noble.com that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & Noble.com does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at BN.com or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation

Reminder:

  • - By submitting a review, you grant to Barnes & Noble.com and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Noble.com Terms of Use.
  • - Barnes & Noble.com reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & Noble.com also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on BN.com. It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

 
Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)