@inproceedings{e7e60a702132486fb7e210b807ca639d,
title = "One-class classification for spontaneous facial expression analysis",
abstract = "In this paper, we explore one-class classification application in recognizing emotional and non-emotional facial expressions occurred in a realistic human conversation setting - Adult Attachment Interview (AAI). Although emotional facial expressions are defined in terms of facial action units in the psychological study, non-emotional facial expressions have not distinct description. It is difficult and expensive to model non-emotional facial expressions. Thus, we treat this facial expression recognition as a one-class classification problem which is to describe target objects (i.e. emotional facial expressions) and distinguish them from outliers (i.e. non-emotional ones). We first apply Kernel whitening to map the emotional data in a kernel subspace with unit variances in all directions. Then, we use Support Vector Data Description (SVDD) for the classification which is to directly fit a boundary with minimal volume around the target data. We present our preliminary experiments on the AAI data, and compare Kernel whitening SVDD with PCA+SVDD and PCA+Gaussian methods.",
author = "Zhihong Zeng and Yun Fu and Roisman, {Glenn I.} and Zhen Wen and Yuxiao Hu and Huang, {Thomas S.}",
year = "2006",
month = nov,
day = "14",
doi = "10.1109/FGR.2006.83",
language = "English (US)",
isbn = "0769525032",
series = "FGR 2006: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition",
pages = "281--286",
booktitle = "FGR 2006",
note = "FGR 2006: 7th International Conference on Automatic Face and Gesture Recognition ; Conference date: 10-04-2006 Through 12-04-2006",
}