@inproceedings{6e2bc9ec7974489285bc1dbcbab8f156,
title = "A study of non-frontal-view facial expressions recognition",
abstract = "The existing methods of facial expression recognition are typically based on the near-frontal face data. The analysis of non-frontal-view facial expression is a largely unexplored research. The accessibility to a recent 3D facial expression database (BU-3DFE database) motivates us to explore an interesting question: whether non-frontal-view facial expression analysis can achieve the same as or better performance than the existing frontal-view facial expression method. Our extensive recognition experiments on data of 100 subjects with yaw rotation view angles suggests that the non-frontal-view facial expression classification can outperform frontal-view facial expression recognition, given the manually labeled facial key points.",
author = "Yuxiao Hu and Zhihong Zeng and Lijun Yin and Xiaozhou Wei and Jilin Tu and Huang, {Thomas S.}",
year = "2008",
doi = "10.1109/icpr.2008.4761052",
language = "English (US)",
isbn = "9781424421756",
series = "Proceedings - International Conference on Pattern Recognition",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2008 19th International Conference on Pattern Recognition, ICPR 2008",
address = "United States",
}