Facial expression analysis from enhanced edge images using gabor wavelets

Abstract

Facial expression analysis is rapidly becoming an area of intense interest in computer science and human-computer interaction design communities. The most expressive way humans display emotions is through facial expressions. In this paper we present a method to analyze facial expression from images by applying Gabor wavelet transform on face images and Principal Component Analysis (PCA) is done on the Gabor coefficients. The weight vectors are compared to get minimum variation. As a second stage, the images are preprocessed to enhance the edge details and non uniform down sampling is done at the Gabor output to reduce the computational complexity and processing time. Our method reliably works even with faces, which carry heavy expressions.