Modeling, Recognizing, and Explaining Apparent Personality from Videos

Hugo Jair Escalante; Heysem Kaya; Albert Ali Salah; Sergio Escalera; Yagmur Gucluturk; Umut Guclu; Xavier Baro; Isabelle Guyon; Julio C.S.Jacques Junior; Meysam Madadi; Stephane Ayache; Evelyne Viegas; Furkan Gurpnar; Achmadnoer Sukma Wicaksana; Cynthia C.S. Liem; Marcel A.J. Van Gerven; Rob Van Lier

doi:10.1109/TAFFC.2020.2973984

Modeling, Recognizing, and Explaining Apparent Personality from Videos

Hugo Jair Escalante^*, Heysem Kaya, Albert Ali Salah, Sergio Escalera, Yagmur Gucluturk, Umut Guclu, Xavier Baro, Isabelle Guyon, Julio C.S.Jacques Junior, Meysam Madadi, Stephane Ayache, Evelyne Viegas, Furkan Gurpnar, Achmadnoer Sukma Wicaksana, Cynthia C.S. Liem, Marcel A.J. Van Gerven, Rob Van Lier

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

22 Citations (Scopus)

Abstract

Explainability and interpretability are two critical aspects of decision support systems. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of apparent personality recognition. To the best of our knowledge, this is the first effort in this direction. We describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, evaluation protocol, proposed solutions and summarize the results of the challenge. We investigate the issue of bias in detail. Finally, derived from our study, we outline research opportunities that we foresee will be relevant in this area in the near future.

Original language	English
Journal	IEEE Transactions on Affective Computing
Volume	13
Issue number	2
Pages (from-to)	894-911
Number of pages	18
ISSN	2371-9850
DOIs	https://doi.org/10.1109/TAFFC.2020.2973984
Publication status	Published - 2022
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2010-2012 IEEE.

Keywords

algorithmic accountability
Explainable computer vision
first impressions
multimodal information
personality analysis

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10.1109/TAFFC.2020.2973984

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Escalante, H. J., Kaya, H., Salah, A. A., Escalera, S., Gucluturk, Y., Guclu, U., Baro, X., Guyon, I., Junior, J. C. S. J., Madadi, M., Ayache, S., Viegas, E., Gurpnar, F., Wicaksana, A. S., Liem, C. C. S., Van Gerven, M. A. J., & Van Lier, R. (2022). Modeling, Recognizing, and Explaining Apparent Personality from Videos. IEEE Transactions on Affective Computing, 13(2), 894-911. https://doi.org/10.1109/TAFFC.2020.2973984

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title = "Modeling, Recognizing, and Explaining Apparent Personality from Videos",

abstract = "Explainability and interpretability are two critical aspects of decision support systems. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of apparent personality recognition. To the best of our knowledge, this is the first effort in this direction. We describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, evaluation protocol, proposed solutions and summarize the results of the challenge. We investigate the issue of bias in detail. Finally, derived from our study, we outline research opportunities that we foresee will be relevant in this area in the near future.",

keywords = "algorithmic accountability, Explainable computer vision, first impressions, multimodal information, personality analysis",

author = "Escalante, {Hugo Jair} and Heysem Kaya and Salah, {Albert Ali} and Sergio Escalera and Yagmur Gucluturk and Umut Guclu and Xavier Baro and Isabelle Guyon and Junior, {Julio C.S.Jacques} and Meysam Madadi and Stephane Ayache and Evelyne Viegas and Furkan Gurpnar and Wicaksana, {Achmadnoer Sukma} and Liem, {Cynthia C.S.} and {Van Gerven}, {Marcel A.J.} and {Van Lier}, Rob",

note = "Publisher Copyright: {\textcopyright} 2010-2012 IEEE.",

year = "2022",

doi = "10.1109/TAFFC.2020.2973984",

language = "English",

volume = "13",

pages = "894--911",

journal = "IEEE Transactions on Affective Computing",

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Escalante, HJ, Kaya, H, Salah, AA, Escalera, S, Gucluturk, Y, Guclu, U, Baro, X, Guyon, I, Junior, JCSJ, Madadi, M, Ayache, S, Viegas, E, Gurpnar, F, Wicaksana, AS, Liem, CCS, Van Gerven, MAJ & Van Lier, R 2022, 'Modeling, Recognizing, and Explaining Apparent Personality from Videos', IEEE Transactions on Affective Computing, vol. 13, no. 2, pp. 894-911. https://doi.org/10.1109/TAFFC.2020.2973984

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AU - Escalante, Hugo Jair

AU - Kaya, Heysem

AU - Salah, Albert Ali

AU - Escalera, Sergio

AU - Gucluturk, Yagmur

AU - Guclu, Umut

AU - Baro, Xavier

AU - Guyon, Isabelle

AU - Junior, Julio C.S.Jacques

AU - Madadi, Meysam

AU - Ayache, Stephane

AU - Viegas, Evelyne

AU - Gurpnar, Furkan

AU - Wicaksana, Achmadnoer Sukma

AU - Liem, Cynthia C.S.

AU - Van Gerven, Marcel A.J.

AU - Van Lier, Rob

PY - 2022

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AB - Explainability and interpretability are two critical aspects of decision support systems. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an introduction to explainability and interpretability in the context of apparent personality recognition. To the best of our knowledge, this is the first effort in this direction. We describe a challenge we organized on explainability in first impressions analysis from video. We analyze in detail the newly introduced data set, evaluation protocol, proposed solutions and summarize the results of the challenge. We investigate the issue of bias in detail. Finally, derived from our study, we outline research opportunities that we foresee will be relevant in this area in the near future.

KW - algorithmic accountability

KW - Explainable computer vision

KW - first impressions

KW - multimodal information

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Modeling, Recognizing, and Explaining Apparent Personality from Videos

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Keywords

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