@inproceedings{731444cb35db4d81a91c4f4ff7dcd2b8,
title = "Facial action unit recognition and inference for facial expression analysis",
abstract = "Human facial expression is extremely abundant, and can be described by numerous facial action units. Recognizing facial action units helps catching the inner emotion or intention of human. In this paper, we propose a novel method for facial action unit recognition and inference. We used Gabor wavelet and optical flow for feature extraction, and used support vector machine and dynamic bayesian network for classification and inference respectively. We combined the advantages of both global and local feature extraction, recognized the most discriminant AUs with multiple classifiers to achieve high recognition rate, and then inference the related AUs. Experiments were conducted on the Cohn-Kanade AU-Coded database. The results demonstrated that compared to early researches for facial action units recognition, our method is capable of recognizing more action units and achieved good performance.",
keywords = "Dynamic bayesian network, Facial action unit recognition, Gabor wavelet, Optical flow, Support vector machine",
author = "Xue, \{Yu Li\} and Xia Mao and Qing Chang",
year = "2012",
language = "英语",
isbn = "9789898565037",
series = "VISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications",
publisher = "Inst. for Syst. and Technol. of Inf., Control and Commun. (INSTICC)",
pages = "694--697",
booktitle = "VISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications",
note = "International Conference on Computer Vision Theory and Applications, VISAPP 2012 ; Conference date: 24-02-2012 Through 26-02-2012",
}