Selecting 3D Curves on the Nasal Surface using AdaBoost for Person Authentication

Abstract

The main contribution of this paper is the use of an AdaBoost-based learning algorithm which builds a strong classifier from a set of weak classifiers associated with level curves in the nasal region of 3D faces. Its main application is person authentication. The basic idea is to represent nasal surfaces using indexed collections of level curves, and to compare shapes of noses by comparing the shape of their corresponding curves. AdaBoost considers each curve as a weak classifier and iteratively selects relevant curves to increase the authentication accuracy. We demonstrate these ideas on a subset taken from FRGC v2 (Face Recognition Grand Challenge) database. The proposed approach increases authentication performances relative to a simple fusion of scores from all curves.