Statistical Face Recognition via a k-Means Iterative Algorithm

A face recognition algorithm based on a iterated k-means classification technique will be presented in this paper. The proposed algorithm, when compared with popular PCA algorithms for face recognition has an improved recognition rate on various benchmark datasets. The presented algorithm, unlike PCA, is not a dimensional reduction algorithm, nonetheless it yields barycentric-faces which can be used to determine different types of face expressions, light conditions and pose. The accuracy of PCA and k-means methods has been evaluated under varying expression, illumination and pose using standard face databases.