Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/68743
Title: A Comparative Study of Facial Emotion Classification
Authors: Hu, T.
De Silva, L.C. 
Issue Date: 2001
Source: Hu, T.,De Silva, L.C. (2001). A Comparative Study of Facial Emotion Classification. Society for Imaging Science and Technology: Image Processing, Image Quality, Image Capture, Systems Conference : 416-420. ScholarBank@NUS Repository.
Abstract: Face plays an important role in communication so automatic recognition of facial emotion is an important addition to computer vision research. This paper presents a comparative study of two types of approaches to facial emotion classification on single images. Gabor wavelets is the technique we employ here to extract features from upper face and lower face. Linear discriminant function (LDF) is applied first for classification. In this type, we compare principle component analysis (PCA) and Fisher linear discriminant (FLD). In the second type of neural network, we focus on multi-layer perceptron (MLP), where single big MLP and multiple MLP classifier are compared. The experimental results show PCA outperforms FLD, and multiple MLPs classifier beats single big MLP. In addition, it is also indicated that Gabor coefficients at high frequency and vertical orientation may contain more information about facial emotion.
Source Title: Society for Imaging Science and Technology: Image Processing, Image Quality, Image Capture, Systems Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/68743
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

36
checked on Mar 9, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.