Face detection and geometric face normalization

Abstract

Face detection is a prerequisite step for face recognition and face analysis related applications. Aim of the face detection system is to identify and locate all faces regardless of their positions, scale, orientation, lighting conditions, expressions, etc. The faces which get detected under such conditions will affect the face recognition rate. Various approaches have been employed to detect faces in images. But as the face detection task is quite complex, each method is build in a precise context. The two main face detection approaches are: image based methods and geometrical based methods. We will focus on a detector which processes images very quickly while achieving high detection rates. This detection is based on a boosting algorithm called AdaBoost and the response of simple Haar-based features used by Viola and Jones. This paper presents a geometric normalization method based on eyes detection using Haar features and AdaBoost algorithm. The proposed method effectively normalizes the in-plane oriented faces and improves the face recognition rate.