Simultaneous Prediction of Valence/Arousal and Emotions on AffectNet, Aff-Wild and AFEW-VA
Author(s) -
Sebastian Handrich,
Laslo Dinges,
Ayoub Al-Hamadi,
Philipp Werner,
Zaher Al Aghbari
Publication year - 2020
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2020.03.134
Subject(s) - valence (chemistry) , computer science , arousal , facial expression , emotion recognition , artificial intelligence , speech recognition , psychology , neuroscience , physics , quantum mechanics
We address the problem of emotional state detection from facial expressions. Our proposed approach simultaneously detects faces and predicts both discrete emotion categories and continuous valence/arousal values from raw input images. We train and evaluate our approach on 3 different datasets, compare our approach to other state-of-the-art approaches and perform a cross-database evaluation. In this way, we found, that our approach generalizes well and is suitable for real-time applications.
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