Recognising Human Emotions from Body Movement and Gesture Dynamics

By Ginevra Castellano, Santiago D. Villalba, Antonio Camurri. Affective Computing and Intelligent Interaction, 2007

375 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Survey on Emotional Body Gesture Recognition (2018, methodology): “[104], [105] collected affective body lan-”
A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances (2022, background): “Hybrid-level [105] M u tim o d al A ffctiv e A n ly is Statistic-based or movement-based [299-302]”
EEG-based classification of positive and negative affective states (2014, methodology): “[5-9] These existing methods, however, are all limited by the main challenge in emotion recognition: observation of external indicators of emotion fail to account for the subconscious component of emotion, thoughts, veiled”
Emotion Recognition through Multiple Modalities: Face, Body Gesture, Speech (2008, methodology): “Facial expressions [12] [13], vocal features [14] [15], body movements and postures [16] [17] [18], physiological signals [19] have been used as inputs during these attempts, while multimodal emotion recognition is currently gaining ground [20] [21] [22].”
A Review of Human Activity Recognition Methods (2015, methodology): “Usually, the terms “activity” and “behavior” are used interchangeably in the literature (Castellano et al., 2007; Song et al., 2012a).”