Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Electronic and Information Engineering | en_US |
| dc.contributor.advisor | Lam, Kenneth (EIE) | - |
| dc.creator | Huang, Ruoxi | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/9565 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Facial expression recognition | en_US |
| dcterms.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. | en_US |
| dcterms.extent | v, 47 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2018 | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.LCSH | Human face recognition (Computer science) | en_US |
| dcterms.LCSH | Image analysis -- Data processing | en_US |
| dcterms.LCSH | Image processing -- Digital techniques | en_US |
| dcterms.accessRights | restricted access | en_US |
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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