Statistics Causality Analysis of Emotions Evoked by Self-Feedback and Facial Features Based on Feature Maps

Open Access

Abstract:  Previous studies have demonstrated that emotional arousal is evoked by visual feedback of a selfie. This selfie was subjectively evaluated as having a good face and a good psychological state. However, the causality between emotional arousal due to feedback from a selfie and facial features recognized by the human eye was not revealed. The objective of the present study was factor clarification of the emotional arousal. The study evaluates the kind of facial information the human eye recognizes when the human distinguishes the type of selfie. For this, a model was developed using machine learning to automatically classify if a photographed selfie can favorably affect the emotional state. As a result, the type of selfie was distinguished at 83.3% correctness, and it was suggested that the whole face was recognized when the human eye evaluated a selfie as a selfie that can have a favorable effect on the emotional state. In other words, when evaluating the face, it was suggested that evaluating the whole, not the part, would be a cause of emotional arousal.

Keywords: Emotion, Emotional Arousal, Machine Learning, Selfie

Genki Kato, Kosuke Oiwa and Akio Nozawa

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Aoyama Gakuin University, Department of Science and Engineering

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Vol.4, Issue 2

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