Fiducial points detection of a face using RBF-SVM and adaboost classification

Abstract

Fiducial points are points that are used as points of reference or measure. Determining of fiducial points can be a fundamental step to recognize a face. A few important fiducial points are the eyes, lip edges, nose, chin etc. Using the fiducial points we can either obtain an outline of the entire face or develop a relationship between the fiducial points themselves to act as a medium to recognize a face. Lot of research has been ongoing in this regard. In this paper the Fiducial points and their existing relationships are studied using a Support Vector Machine with a Radial basis Function kernel. New images when tested showed a high accuracy of correct results in terms of the actual positions of the fiducial points in the image. Further classification of the fiducial points is done using an Adaboost classification to improve the accuracy.