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CorrFeat : Correlation-based feature extraction algorithm using skin conductance and pupil diameter for emotion recognition. / Zhang, Tianyi; Ali, Abdallah El; Wang, Chen; Zhu, Xintong; Cesar, Pablo.

ICMI'19 : Proceedings of the 2019 International Conference on Multimodal Interaction. ed. / Wen Gao; Helen Mei Ling Meng; Matthew Turk; Susan R. Fussell; Bjorn Schuller; Bjorn Schuller; Yale Song; Kai Yu. New York : Association for Computing Machinery (ACM), 2019. p. 404-408.

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Harvard

Zhang, T, Ali, AE, Wang, C, Zhu, X & Cesar, P 2019, CorrFeat: Correlation-based feature extraction algorithm using skin conductance and pupil diameter for emotion recognition. in W Gao, HM Ling Meng, M Turk, SR Fussell, B Schuller, B Schuller, Y Song & K Yu (eds), ICMI'19 : Proceedings of the 2019 International Conference on Multimodal Interaction. Association for Computing Machinery (ACM), New York, pp. 404-408, 21st ACM International Conference on Multimodal Interaction, ICMI 2019, Suzhou, China, 14/10/19. https://doi.org/10.1145/3340555.3353716

APA

Zhang, T., Ali, A. E., Wang, C., Zhu, X., & Cesar, P. (2019). CorrFeat: Correlation-based feature extraction algorithm using skin conductance and pupil diameter for emotion recognition. In W. Gao, H. M. Ling Meng, M. Turk, S. R. Fussell, B. Schuller, B. Schuller, Y. Song, & K. Yu (Eds.), ICMI'19 : Proceedings of the 2019 International Conference on Multimodal Interaction (pp. 404-408). Association for Computing Machinery (ACM). https://doi.org/10.1145/3340555.3353716

Vancouver

Zhang T, Ali AE, Wang C, Zhu X, Cesar P. CorrFeat: Correlation-based feature extraction algorithm using skin conductance and pupil diameter for emotion recognition. In Gao W, Ling Meng HM, Turk M, Fussell SR, Schuller B, Schuller B, Song Y, Yu K, editors, ICMI'19 : Proceedings of the 2019 International Conference on Multimodal Interaction. New York: Association for Computing Machinery (ACM). 2019. p. 404-408 https://doi.org/10.1145/3340555.3353716

Author

Zhang, Tianyi ; Ali, Abdallah El ; Wang, Chen ; Zhu, Xintong ; Cesar, Pablo. / CorrFeat : Correlation-based feature extraction algorithm using skin conductance and pupil diameter for emotion recognition. ICMI'19 : Proceedings of the 2019 International Conference on Multimodal Interaction. editor / Wen Gao ; Helen Mei Ling Meng ; Matthew Turk ; Susan R. Fussell ; Bjorn Schuller ; Bjorn Schuller ; Yale Song ; Kai Yu. New York : Association for Computing Machinery (ACM), 2019. pp. 404-408

BibTeX

@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",
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'19",
publisher = "Association for Computing Machinery (ACM)",
address = "United States",
note = "21st ACM International Conference on Multimodal Interaction, ICMI 2019 ; Conference date: 14-10-2019 Through 18-10-2019",

}

RIS

TY - GEN

T1 - CorrFeat

T2 - 21st ACM International Conference on Multimodal Interaction, ICMI 2019

AU - Zhang, Tianyi

AU - Ali, Abdallah El

AU - Wang, Chen

AU - Zhu, Xintong

AU - Cesar, Pablo

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Emotion recognition

KW - Machine learning

KW - MAHNOB-HCI database

KW - Pupil diameter

KW - Skin conductance response

UR - http://www.scopus.com/inward/record.url?scp=85074906351&partnerID=8YFLogxK

U2 - 10.1145/3340555.3353716

DO - 10.1145/3340555.3353716

M3 - Conference contribution

SN - 978-1-4503-6860-5

SP - 404

EP - 408

BT - ICMI'19

A2 - Gao, Wen

A2 - Ling Meng, Helen Mei

A2 - Turk, Matthew

A2 - Fussell, Susan R.

A2 - Schuller, Bjorn

A2 - Schuller, Bjorn

A2 - Song, Yale

A2 - Yu, Kai

PB - Association for Computing Machinery (ACM)

CY - New York

Y2 - 14 October 2019 through 18 October 2019

ER -

ID: 66953562