PT Journal
AU Hugo Jair Escalante
   Heysem Kaya
   Albert Ali Salah
   Sergio Escalera
   Yagmur Gucluturk
   Umut Guçlu
   Xavier Baro
   Isabelle Guyon
   Julio C. S. Jacques Junior
   Meysam Madadi
   Stephane Ayache
   Evelyne Viegas
   Furkan Gurpinar
   Achmadnoer Sukma Wicaksana
   Cynthia Liem
   Marcel A. J. Van Gerven
   Rob Van Lier
TI Modeling, Recognizing, and Explaining Apparent Personality from Videos
SO IEEE Transactions on Affective Computing
JI TAC
PY 2022
BP 894
EP 911
VL 13
IS 2
DI 10.1109/TAFFC.2020.2973984
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.
ER