Optimal Weighting of Landmarks for Face Recognition

Abstract

A new method named Landmark Model Matching was recently proposed for fully automatic face recognition. It was inspired by Elastic Bunch Graph Matching and Active Shape Model. Landmark Model Matching consists of four phases: creation of the landmark distribution model, face finding, landmark finding, and recognition. A drawback in Landmark Model Matching is that, in the recognition phase, the weights given to different landmarks or facial feature points were determined experimentally. In this work, we optimized the weights given to landmarks, and thereby improved the recognition rates for the two benchmarks used.