A Probabilistic Fitness Measure for Deformable Template Models
Jane Haslam, Chris Taylor, Tim F. Cootes · 1994
Methods for automatic image interpretation based on the use of deformable template models have proved very successful. Whatever deformable template scheme is used, one of the basic requirements is a method for assessing the likelihood that a particular model instance is the correct interpretation of a given image. We describe a Bayesian `fitness' measure which combines the likelihood of the model shape with the evidential support in a principled way. Image search is carried out by minimising the fitness measure using multi-scale quasi-Newtonian optimisation. We have previously compared the perform# ance of different fitness measures. Here we give results for the new method and show that, by making optimal use of the image evidence, it achieves more accurate interpreta# tion than the best of the methods we have previously tested. Introduction Flexible template models have been used successfully for many applications of automatic image interpretation[1,2,3,4]. The template embodies ÁÂÄ...