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Continuous body emotion recognition system during theater performances
Author(s) -
Senecal Simon,
Cuel Louis,
Aristidou Andreas,
MagnenatThalmann Nadia
Publication year - 2016
Publication title -
computer animation and virtual worlds
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 49
eISSN - 1546-427X
pISSN - 1546-4261
DOI - 10.1002/cav.1714
Subject(s) - computer science , gesture , motion (physics) , facial expression , expression (computer science) , artificial intelligence , motion capture , ideal (ethics) , dynamics (music) , biological motion , human–computer interaction , gesture recognition , computer vision , psychology , pedagogy , philosophy , epistemology , programming language
Understanding emotional human behavior in its multimodal and continuous aspect is necessary for studying human machine interaction and creating constituent social agents. As a first step, we propose a system for continuous emotional behavior recognition expressed by people during communication based on their gesture and their whole body dynamical motion. The features used to classify the motion are inspired by the Laban Movement Analysis entities [11][von Laban R, 1988] and are mapped onto the well‐known Russell Circumplex Model [4][Russell JA, 1980]. We choose a specific case study that corresponds to an ideal case of multimodal behavior that emphasizes the body motion expression: theater performance. Using a trained neural network and annotated data, our system is able to describe the motion behavior as trajectories on the Russell Circumplex Model diagram during theater performances over time. This work contributes to the understanding of human behavior and expression and is a first step through a complete continuous emotion recognition system whose next step will be adding facial expressions. Copyright © 2016 John Wiley & Sons, Ltd.