Fondazione Bruno Kessler - Technologies of Vision

contains material from
Template Matching Techniques in Computer Vision: Theory and Practice
Roberto Brunelli 2009 John Wiley & Sons, Ltd

Chapter 13
Feature Templates

Many applications in image processing rely on robust detection of image features and accurate estimation of their parameters. Features may be too numerous to justify the process of deriving a new detector for each one. This chapter exploits principal components analysis to build a single, flexible, and efficient detection mechanism based on the use of composite rejectors. The complementary aspect of detecting templates considered as a set of separate features will also be addressed presenting an efficient architecture: a rejector cascade classifier built by boosting simple, pixel level classifiers applied to a census transformed image.

keywords: parametric feature manifold, AdaBoost, boosting, census transform, multi-class pattern rejector, constellation matching