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Modeling, Recognizing, and Explaining Apparent Personality From Videos

Hugo Jair Escalante, Heysem Kaya, Albert Ali Salah, Sérgio Escalera, Yağmur Güçlütürk, Umut Guclu, Xavier Baró, Isabelle Guyon, Julio C. S. Jacques, Meysam Madadi, Stéphane Ayache, Evelyne Viegas, Furkan Gurpnar, Achmadnoer Sukma Wicaksana, Cynthia C. S. Liem, Marcel van Gerven, Rob van Lier

2020IEEE Transactions on Affective Computing97 citationsDOIOpen Access PDF

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.

Topics & Concepts

InterpretabilityContext (archaeology)PersonalitySet (abstract data type)Computer scienceProtocol (science)Data scienceArtificial intelligenceBig Five personality traitsMachine learningPsychologySocial psychologyPaleontologyMedicineProgramming languagePathologyBiologyAlternative medicineHuman Pose and Action RecognitionGenerative Adversarial Networks and Image SynthesisVideo Analysis and Summarization