@inproceedings{dabc1bbbfe10483f96507430914c2b75,
title = "Automatic facial expression recognition with AAM-based feature extraction and SVM classifier",
abstract = "In this paper, an effective method is proposed for automatic facial expression recognition from static images. First, a modified Active Appearance Model (AAM) is used to locate facial feature points automatically. Then, based on this, facial feature vector is formed. Finally, SVM classifier with a sample selection method is adopted for expression classification. Experimental results on the JAFFE database demonstrate an average recognition rate of 69.9% for novel expressers, showing that the proposed method is promising.",
author = "Xiaoyi Feng and Baohua Lv and Zhen Li and Jiling Zhang",
year = "2006",
doi = "10.1007/11925231_69",
language = "英语",
isbn = "3540490264",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "726--733",
booktitle = "MICAI 2006",
note = "5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence ; Conference date: 13-11-2006 Through 17-11-2006",
}