A Fast Facial Expression Recognition Method at Low-Resolution Images

Abstract

In this paper, we propose a novel image-based facial expression recognition method called "expression transition" to identify six kinds of facial expressions (anger, fear, happiness, neutral, sadness, and surprise) at low-resolution images. Two approaches: direct mapping and singular value decomposition (SVD) are applied to calculate the expression transition matrices. The transformed images with a set of expression transition matrices are compared to identify the facial expressions. The experimental results show that the proposed facial expression recognition system can recognize 120 test images in the Chon-Kanade facial expression database with high accuracy and efficiency.