Study on Detection and Recognition of Faces in Images Using Eigenspace and GAT Correlation

Abstract

This paper describes two different approaches to the problem of face detection and recognition. One approach determines locations of right and left eyes, nose, and mouth in an input image using Maximum Likelihood detection, and, then, recognizes the obtained canonical face image using a simple distance classifier based on the eigenspace method. The other approach applies the global affine transformation (GAT) correlation technique to matching of the input image and enrolled face templates. The GAT correlation technique simultaneously detects and recognizes a face candidate region by determining the affine-invariant correlation value between two images. We show successful experimental results made on 300 faces × 8 images extracted from the public HOIP face image database.