Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coding, Analysis, Interpretation, and Recognition of Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Analysis of Facial Expressions: The State of the Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Action Units for Facial Expression Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating realistic facial expressions with wrinkles for model-based coding
Computer Vision and Image Understanding
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Automatic recognition of human facial expressions
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
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This paper explores the use of facial wrinkle textures for recognizing the facial expressions. Based on the observation of the wrinkles appearance and change along with performed expressions, we propose to extract the partial texture information in both the facial organ areas (e.g., eyes and mouth) and the facial wrinkle areas, and use the texture dissimilarity between the neutral expression and the active expression to extract the active texture for the expression representation. We present a novel method using multiple levels of detail to measure the active texture dissimilarity. The rate of change between levels is used as the rule for discriminating 6 types of universal expressions. The experiments on video sequences demonstrate the simplicity and efficiency of the proposed method for recognizing expressions with an 82.8% correct recognition rate.