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http://dx.doi.org/10.15701/kcgs.2018.24.4.1

Emotion Training: Image Color Transfer with Facial Expression and Emotion Recognition  

Kim, Jong-Hyun (Kangnam University)
Publication Information
Journal of the Korea Computer Graphics Society / v.24, no.4, 2018 , pp. 1-9 More about this Journal
Abstract
We propose an emotional training framework that can determine the initial symptom of schizophrenia by using emotional analysis method through facial expression change. We use Emotion API in Microsoft to obtain facial expressions and emotion values at the present time. We analyzed these values and recognized subtle facial expressions that change with time. The emotion states were classified according to the peak analysis-based variance method in order to measure the emotions appearing in facial expressions according to time. The proposed method analyzes the lack of emotional recognition and expressive ability by using characteristics that are different from the emotional state changes classified according to the six basic emotions proposed by Ekman. As a result, the analyzed values are integrated into the image color transfer framework so that users can easily recognize and train their own emotional changes.
Keywords
Image color transfer; Schizophrenia; Emotion training; Facial expression; Emotion recognition;
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