Modeling, Recognizing, and Explaining Apparent Personality from Videos
Escalante, Hugo Jair; Kaya, Heysem; Salah, Albert Ali; Escalera, Sergio; Gucluturk, Yagmur; Guclu, Umut; Baro, Xavier; Guyon, Isabelle; Jacques, Julio C.S.; Madadi, Meysam; Ayache, Stephane; Viegas, Evelyne; Gurpinar, Furkan; Wicaksana, Achmadnoer Sukma; Liem, Cynthia; Van Gerven, Marcel A.J.; Van Lier, Rob
(2022) IEEE Transactions on Affective Computing, volume 13, issue 2, pp. 894 - 911
(Article)
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
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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.
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Keywords: Algorithmic accountability, Computational modeling, Computer vision, Explainable computer vision, Face, First impressions, Interviews, Multimodal information, Personality analysis, Predictive models, Videos, Visualization, Taverne, Software, Human-Computer Interaction
ISSN: 1949-3045
Publisher: Institute of Electrical and Electronics Engineers Inc.
(Peer reviewed)
