Template Matching Techniques in Computer Vision (PDF)

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 2.2 Biological Eyes 2.3 Digital Eyes 2.4 Digital Image Representations 2.5 Bibliographical Remarks References 3 Template Matching as Testing 3.1 Detection and Estimation 3.2 Hypothesis Testing 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 3.7 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 5.2 Non-parametric Local Transforms 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 8.2 A Nonlinear Approach: Kernel PCA 8.3 Independent Components 8.4 Linear Discriminant Analysis 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 Diffeomorphic Matching 9.5 Bibliographical Remarks References 10 Computational Aspects of Template Matching 10.1 Speed 10.2 Precision 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

Roberto Brunelli, Senior Researcher, ITC-irst, Italy
Roberto Brunelli is currently working for ITC-irst for the Technologies of Vision Research Line of Interactive Sensory Systems Division. He has held this post since 1987 after gaining his degree in Physics from the University of Trento (Italy). His research activities and interests are in the areas of computer vision tools, analysis of aerial images, the development of algorithms for the compressed description of binary images, optimization, neural networks, face analysis, video analysis and image retrieval. Dr Brunelli's research projects have been implemented in several EU funded projects, and he has also undertaken teaching assignments at the International Doctorate School of the University of Trento. He has written over 30 published journal and conference papers, several of which deal with computational face perception. The paper 'Template Matching: Matched Spatial Filters and Beyond' received a Pattern Recognition Society Award in 1998. He has acted as a referee for some of the major journals on image processing and related techniques, for example Computer Vision and Image Understanding and IEEE Transactions on Image Processing, and has also been on the Technical Committee for several conferences, including Audio- and Video-Based Biometric Person Authentication, IEEE Conference on Computer Vision and Pattern Recognition and European Conference on Computer Vision.

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