Emotion Expression in Human Body Posture and Movement: A Survey on Intelligible Motion Factors, Quantification and Validation

Abstract

Many areas in computer science are facing the need to analyze, quantify and reproduce movements expressing emotions. This paper presents a systematic review of the intelligible factors involved in the expression of emotions in human movement and posture. We have gathered the works that have studied and tried to identify these factors by sweeping many disciplinary fields such as psychology, biomechanics, choreography, robotics and computer vision. These researches have each used their own definitions, units and emotions, which prevents a global and coherent vision. We propose a meta-analysis approach that cross-references and aggregates these researches in order to have a unified list of expressive factors quantified for each emotion. A calculation method is then proposed for each of the expressive factors and we extract them from an emotionally annotated animation dataset: Emilya. The comparison between the results of the meta-analysis and the Emilya analysis reveals high correlation rates, which validates the relevance of the quantified values obtained by both methodologies. The analysis of the results raises interesting perspectives for future research in affective computing.

Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion

“…Recently, there have been some other surveys and reviews on artificial EQ (AEI), such as facial expression recognition (FER) [ 3 ], [ 4 ], [ 5 ], [ 6 ], microexpression recognition (MER) [ 7 ], [ 8 ], [ 9 ], textual sentiment classification [ 10 ], [ 11 ], [ 12 ], music and speech emotion recognition [ 13 ], [ 14 ], [ 15 ], affective image content analysis [ 16 ], emotional body gesture recognition [ 17 ], bodily expressed emotion recognition [ 18 ], emotion recognition from physiological signals [ 19 ], [ 20 ], multimodal emotion recognition [ 21 ], [ 22 ], and affective theory use [ 23 ]. These articles mainly focus on emotion and sentiment analysis for a specific modality from the perspective of machine learning and pattern recognition or focus on the psychological emotion theories.…”