Modeling, Recognizing, and Explaining Apparent Personality from Videos
Hugo Jair Escalante (INAOE, Cinvestav)
H Kaya (Universiteit Utrecht)
Albert Ali Salah (Universiteit Utrecht)
Sergio Escalera (Universitat Politecnica de Catalunya)
Yağmur Güçlütürk (Radboud Universiteit Nijmegen)
Umut Güçlü (Radboud Universiteit Nijmegen)
X. Baro (Universitat Politecnica de Catalunya)
Sukma Sukma Wicaksana (Student TU Delft)
CCS Liem (Multimedia Computing)
G.B. Cavadini (External organisation)
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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.