@inproceedings{406c3cad7e204fd7a9d338e301ebb6fa,
title = "Expression intensity recognition based on multilayer hybrid classifier",
abstract = "In this paper, an automatic system for recognizing expression intensity is proposed. Modified Active Appearance Model (MAAM) is utilized to extract facial feature points (FFPs), and then, according to the FFPs' position, the sequence is preprocessed. Coarse-to-fine pyramid algorithm is employed to track FFPs for extracting 23 optical flow vectors, and eliminating the error caused by rigid movement of head. Expression intensity is recognized by multilayer hybrid classifier. Support Vector Machine (SVM) classifies the expression in the form of optical flow vectors, and KNN classifier recognizes the intensity. We conduct the experiments on Cohn-Kanade expression database and the result shows good effect.",
keywords = "Expression intensity recognition, KNN, MAAM, SVM, optical flow vector",
author = "Xia Mao and Chongping Wang and Yuli Xue",
year = "2013",
doi = "10.1007/978-3-642-33932-5\_69",
language = "英语",
isbn = "9783642339318",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
number = "VOL. 2",
pages = "739--748",
booktitle = "Intelligent Autonomous Systems 12 - Proceedings of the 12th International Conference, IAS 2012",
address = "德国",
edition = "VOL. 2",
note = "12th International Conference on Intelligent Autonomous Systems, IAS 2012 ; Conference date: 26-06-2012 Through 29-06-2012",
}