Automatic Facial Feature Extraction and Facial Expression Recognition

Authors:
Séverine Dubuisson;Franck Davoine;Jean Pierre Cocquerez
Affiliations:
-;-;-
Venue:
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Year:
2001

Citing 6
Cited 1

Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow

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Classifying Facial Actions

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Automatic Classification of Single Facial Images

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The FERET Verification Testing Protocol for Face Recognition Algorithms

FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Comprehensive Database for Facial Expression Analysis

FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Eigenfaces for recognition

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Visual learning of texture descriptors for facial expression recognition in thermal imagery

Computer Vision and Image Understanding

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Abstract

In this paper, we present an automatic algorithm for facial expression recognition. We first propose a method for automatic facial feature extraction, based on the analysis of outputs of local Gabor filters. Such analysis is done using a spatial adaptive triangulation of the magnitude of the filtered images. Then, we propose a classification procedure for facial expression recognition, considering the internal part of registered still faces. Principal Component Analysis allows to represent faces in a low-dimensional space, defined by basis functions that are adapted to training sets of facial expressions. We show how to select the best basis functions for facial expression recognition, providing a good linear discrimination: results prove the robustness of the recognition method.