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Authors: Jingying Chen ; Mulan Zhang ; Xianglong Xue ; Ruyi Xu and Kun Zhang

Affiliation: Central China Normal University, China

Keyword(s): Hierarchical Random Forests, Facial Expression Recognition, Facial Action Unit.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Image Understanding ; Pattern Recognition

Abstract: Facial expression recognition is important in natural human-computer interaction, research in this direction has made great progress. However, recognition in noisy environments still remains challenging. To improve the efficiency and accuracy of the expression recognition in noisy environments, this paper presents a hierarchical random forest model based on facial action units (AUs). First, an AUs based feature extraction method is proposed to extract facial feature effectively; second, a hierarchical random forest model based on different AU regions is developed to recognize the expressions in a coarse-to-fine way. The experiment results show that the proposed approach has a good performance in different environments.

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Paper citation in several formats:
Chen, J.; Zhang, M.; Xue, X.; Xu, R. and Zhang, K. (2017). An Action Unit based Hierarchical Random Forest Model to Facial Expression Recognition. In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-222-6; ISSN 2184-4313, SciTePress, pages 753-760. DOI: 10.5220/0006274707530760

@conference{icpram17,
author={Jingying Chen. and Mulan Zhang. and Xianglong Xue. and Ruyi Xu. and Kun Zhang.},
title={An Action Unit based Hierarchical Random Forest Model to Facial Expression Recognition},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2017},
pages={753-760},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006274707530760},
isbn={978-989-758-222-6},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - An Action Unit based Hierarchical Random Forest Model to Facial Expression Recognition
SN - 978-989-758-222-6
IS - 2184-4313
AU - Chen, J.
AU - Zhang, M.
AU - Xue, X.
AU - Xu, R.
AU - Zhang, K.
PY - 2017
SP - 753
EP - 760
DO - 10.5220/0006274707530760
PB - SciTePress

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