This master thesis examines the use of a multi resolution Active Shape Model (ASM) applied on facial features, utilizing the Viola/Jones face detector. The method, initially introduced by Cootes, et al., requires good initial pose parameter values for placing a face model from its local system to the image’s system. This is one of the most critical parts of the process from which the convergence of the method depends on. For this reason, the Viola/Jones detector kicked in, to initially detect the face and subsequently estimate the initial pose parameters for positioning the face model in the search image. The testing of the face detector as well as the quality of the model’s initial position was executed on face images provided by the Milborrow University of Cape Town (MUCT) online database. For building a face model, a set of training images provided by Cootes was used and the search images were chosen randomly from the same training set.
Experiments made initially on some frontal upright images, showed that the face detector succeeded in all images and the placement of the face model was quite accurate in most cases. Subsequently, the quality of the model fit using the multi resolution active shape model approach, showed that the method converged quite well for the inner part of the face but in the outer part, in some cases, was not that precise.