Automatic facial expression recognition

Authors:
Huchuan Lu;Pei Wu;Hui Lin;Deli Yang
Affiliations:
School of Electronic and Information Engineering, Dalian University of Technology, Dalian, Liaoning Province, China;School of Electronic and Information Engineering, Dalian University of Technology, Dalian, Liaoning Province, China;School of Electronic and Information Engineering, Dalian University of Technology, Dalian, Liaoning Province, China;School of Electronic and Information Engineering, Dalian University of Technology, Dalian, Liaoning Province, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

Citing 3
Cited 0

Comprehensive Database for Facial Expression Analysis

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Classifying Facial Attributes Using a 2-D Gabor Wavelet and Discriminant Analysis

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Working Set Selection Using Second Order Information for Training Support Vector Machines

The Journal of Machine Learning Research

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Abstract

We present a fully automatic real time system for face detection and basic facial expression recognition from video and images. The system automatically detects frontal faces in the video stream or images and classifies each of them into 7 expressions. Each video frame is first scanned in real time to detect upright-frontal faces. The faces found are scaled into image patches of equal size and sent downstream for further processing. Gabor energy filters are applied at the scaled image patches followed by a recognition engine. Best results are obtained by selecting a subset of Gabor features using AdaBoost and then training Support Vector Machines on the outputs of the features selected by AdaBoost.