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Emotion Recognition Using Feature-level Fusion of Facial Expressions and Body Gestures

Tanya Keshari, Suja Palaniswamy

Year
2019
Citations
61

Abstract

Automatic emotion recognition using computer vision is significant for many real-world applications like photojournalism, virtual reality, sign language recognition, and Human Robot Interaction (HRI) etc., Psychological research findings advocate that humans depend on the collective visual conduits of face and body to comprehend human emotional behaviour. Plethora of studies have been done to analyse human emotions using facial expressions, EEG signals and speech etc., Most of the work done was based on single modality. Our objective is to efficiently integrate emotions recognized from facial expressions and upper body pose of humans using images. Our work on bimodal emotion recognition provides the benefits of the accuracy of both the modalities.

Keywords

GestureFacial expressionModalitiesComputer scienceFeature (linguistics)Emotion recognitionSign languageModality (human–computer interaction)Body languageArtificial intelligence

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