- Volume 14 Issue 10
DOI QR Code
Emotion Classification Method Using Various Ocular Features
다양한 눈의 특징 분석을 통한 감성 분류 방법
- Received : 2014.06.25
- Accepted : 2014.10.14
- Published : 2014.10.28
In this paper, emotion classification was performed by using four ocular features extracted from near-infrared camera image. According to comparing with previous work, the proposed method used more ocular features and each feature was validated as significant one in terms of emotion classification. To minimize side effects on ocular features caused by using visual stimuli, auditory stimuli for causing two opposite emotion pairs such as "positive-negative" and "arousal-relaxation" were used. As four features for emotion classification, pupil size, pupil accommodation rate, blink frequency, and eye cloased duration were adopted which could be automatically extracted by using lab-made image processing software. At result, pupil accommodation rate and blink frequency were statistically significant features for classification arousal-relaxation. Also, eye closed duration was the most significant feature for classification positive-negative.
Supported by : 상명대학교
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