@inproceedings{a2d39b09266d47c6927a459c95fcf8eb,
title = "A study on emotion recognition based on hierarchical adaboost multi-class algorithm",
abstract = "Researches on human emotion recognition have attracted more and more people{\textquoteright}s interest. Adaboost algorithm is an integrated algorithm that constructs strong classifiers by iterative aggregation of weak classifiers. This paper proposes a hierarchical Adaboost (HAdaboost) multi-class algorithm for emotion recognition, which improves the original Adaboost algorithm. The valence and arousal in different emotional states are used as classification features, and emotion recognition is performed according to their differences. Simulation experiments on the Chinese Facial Affective Picture System (CFAPS) data set demonstrate three types of emotions and seven types of emotions can be distinguished, and the average accuracy rates are 93% and 92.4% respectively.",
keywords = "Emotion recognition, Hierarchical adaboost multi-class algorithm, Integrated weak classifier",
author = "Song Zhang and Bin Hu and Tiantian Li and Xiangwei Zheng",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 18th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2018 ; Conference date: 15-11-2018 Through 17-11-2018",
year = "2018",
doi = "10.1007/978-3-030-05054-2_8",
language = "English",
isbn = "9783030050535",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "105--113",
editor = "Jaideep Vaidya and Jin Li",
booktitle = "Algorithms and Architectures for Parallel Processing - 18th International Conference, ICA3PP 2018, Proceedings",
address = "Germany",
}