|Facial expression recognition
|Lam, Kenneth (EIE)
|Hong Kong Polytechnic University -- Dissertations
Human face recognition (Computer science)
Image analysis -- Data processing
Image processing -- Digital techniques
|Department of Electronic and Information Engineering
|v, 47 pages : color illustrations
|"A facial expression is worth a thousand words", which implies that a human facial expression contains abundant and useful information. Thus there are a big deal of applications on it, such as emotion analysis, advertisement, criminal interrogation and social entertainment. In this thesis, I will give a introduction of the facial expression recognition system. First I will present the methods for face aquisition, this section is mainly about digital image processing techniques. Followed by introducing concepts of some state-of-the-art feature descriptors and classifiers. Feature descriptors will include local binary pattern(LBP), pyramid histogram of gradient(PHOG), local phrase quantization(LPQ). In addition, I will try to use feature fusion method called canonical correlation analysis(CCA) to enhance the features' performance. In the chapter of classifier, it covers k nearest neighbors(kNN), support vector machine(SVM), random forest and gradient boosting. Finally, I will implement and evaluate some combinations among them and attempt to analyze the experiment results to identify the best solution for the facial expression recognition and draw conclusions.
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