An Optical Flow Feature-based Robust Facial Expression Recognition with Hmm from Video
نویسندگان
چکیده
In this work, a novel method is proposed to recognize several facial expressions from time-sequential facial expression images. To produce robust facial expression features, optical flow extraction is utilized which are further improved by Principal Component Analysis (PCA) and Generalized Discriminant Analysis (GDA). Using these features, discrete Hidden Markov Models (HMMs) are utilized to model different facial expressions. Performance of our proposed FER system is compared against the conventional approaches and the proposed approach significantly improves the performance yielding the mean recognition rate of 99.16% whereas the conventional methods yield 82.92% at best.
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