@inproceedings{93f49b118e6a46bc884a6ee0ac1fd448,
title = "CorrFeat: Correlation-based feature extraction algorithm using skin conductance and pupil diameter for emotion recognition",
abstract = "To recognize emotions using less obtrusive wearable sensors, we present a novel emotion recognition method that uses only pupil diameter (PD) and skin conductance (SC). Psychological studies show that these two signals are related to the attention level of humans exposed to visual stimuli. Based on this, we propose a feature extraction algorithm that extract correlation-based features for participants watching the same video clip. To boost performance given limited data, we implement a learning system without a deep architecture to classify arousal and valence. Our method outperforms not only state-of-art approaches, but also widely-used traditional and deep learning methods.",
keywords = "Emotion recognition, Machine learning, MAHNOB-HCI database, Pupil diameter, Skin conductance response",
author = "Tianyi Zhang and Ali, {Abdallah El} and Chen Wang and Xintong Zhu and Pablo Cesar",
year = "2019",
doi = "10.1145/3340555.3353716",
language = "English",
isbn = "978-1-4503-6860-5",
series = "ICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction",
publisher = "Association for Computing Machinery (ACM)",
pages = "404--408",
editor = "Wen Gao and {Ling Meng}, {Helen Mei} and Matthew Turk and Fussell, {Susan R.} and Bjorn Schuller and Bjorn Schuller and Yale Song and Kai Yu",
booktitle = "ICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction",
address = "United States",
note = "21st ACM International Conference on Multimodal Interaction, ICMI 2019 ; Conference date: 14-10-2019 Through 18-10-2019",
}