@inproceedings{b97488e19e7844c68720021b59283c55,
title = "Combining appearance and geometric features for facial expression recognition",
abstract = "This paper introduces a method for facial expression recognition combining appearance and geometric facial features. The proposed framework consistently combines multiple facial representations at both global and local levels. First, covariance descriptors are computed to represent regional features combining various feature information with a low dimensionality. Then geometric features are detected to provide a general facial movement description of the facial expression. These appearance and geometric features are combined to form a vector representation of the facial expression. The proposed method is tested on the CK+ database and shows encouraging performance.",
keywords = "Geometric features, covariance descriptors, facial expression, facial patches",
author = "Hui Yu and Honghai Liu",
note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; 6th International Conference on Graphic and Image Processing, ICGIP 2014 ; Conference date: 24-10-2014 Through 26-10-2014",
year = "2015",
doi = "10.1117/12.2179066",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "David Zhang and Yulin Wang and Xudong Jiang",
booktitle = "Sixth International Conference on Graphic and Image Processing, ICGIP 2014",
address = "美国",
}