Locating landmarks using templates

Abstract

This paper examines different approaches to classification and discrimination applied to two-dimensional (2D) grey-scale images of faces. The database containing 212 standardized images is divided to a training set and a validation set. The aim is the automatic localization of the mouth. We focus on template matching and compare the results with standard classification methods. We discuss the choice of a suitable template and inspect its robustness aspects.

While methods of image analysis are well-established, there exists a popular belief that statistical methods cannot handle this task. We ascertain that simple methods are successful even without a prior reduction of dimension and feature extraction. Template matching and linear discriminant analysis turn out to give very reliable results.