| Author: | Huang, Ruoxi |
| Title: | Facial expression recognition |
| Advisors: | Lam, Kenneth (EIE) |
| Degree: | M.Sc. |
| Year: | 2018 |
| Subject: | Hong Kong Polytechnic University -- Dissertations Human face recognition (Computer science) Image analysis -- Data processing Image processing -- Digital techniques |
| Department: | Department of Electronic and Information Engineering |
| Pages: | v, 47 pages : color illustrations |
| Language: | English |
| Abstract: | "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. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 991022144625503411.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 1.9 MB | Adobe PDF | View/Open |
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