Emotion Classification Method Using Various Ocular Features

다양한 눈의 특징 분석을 통한 감성 분류 방법

  • 김윤경 (상명대학교 대학원 컴퓨터과학과) ;
  • 원명주 (상명대학교 대학원 감성공학과) ;
  • 이의철 (상명대학교 컴퓨터과학과)
  • 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


  1. 이의철, "시각 자극에 의한 감성 반응의 정량적 측정을 위한 카메라 비젼 시스템", 제23회 영상처리 및 이해에 관한 워크샵, 제주그랜드호텔, 2011(2).
  2. H. Heo, E. Lee, J. Woo, C. Kim, K. Park, and M. Whang, "Realistic game system using Multi-Modal user interface," IEEE Transaction on Consumer Electronics, Vol.56, Issue.3, pp.1364-1372, 2010(8).
  3. T. Partala and V. Surakka, "Pupil size variation as an indication of affective processing," Int. J. Human-Computer Studies, Vol.59, Issue.1-2, pp.185-198, 2003(7).
  4. Y. Song, L. Morency, and R. Davis, "Learning a Sparse Codebook of Facial and Body Microexpressions for Emotion Recognition," ICMI, pp.237-244, 2013(12).
  5. H. Gunes and M. Piccardi, "Bi-modal emotion recognition from expressive face and body gesture," J. of Network and Computer Applications, Vol.30, Issue.4, pp.1334-1345, 2007(9).
  6. P. Ekman, R. Levenson, and W. Friesen, "Autonomic nervous system activity distinguishes among emotions," Science New Series, Vol.221, No.4616, pp.1280-1210, 1983(9).
  7. S. Kawai, H. Takano, and K. Nakamura, "Pupil Diameter Variation in Positive and Negative Emotions with Visual Stimulus," IEEE Int. C, pp.13-16, 2013(10).
  8. 엄진섭, 박광배, 손진훈, "ERP와 동공 반응을 이용한 숨긴정보검사", Korean J. of the science of Emotion & sensibility, Vol.15, No.2, pp.259-268, 2012.
  9. 이재화, 이건표, "제품 사용 환경의 사용자 초기 감성 측정 방법에 관한 연구", Korean J. of the science of Emotion & sensibility, Vol.13, No.1, pp.111-120, 2010.
  10. M. Miyao, S. Hacisalihzade, and J. Allen, "Effects of VDT resolution on eyestrain and readability: an eye movement approach," Ergonomics, Vol.32, Issue.6, pp.603-614, 2007(5).
  11. K. Kaneko and K. Sakamoto, "Spontaneous blinks as a criterion of visual fatigue during prolonged work on visual display terminals," Perceptual and Motor Skills, Vol.92, Issue.1, pp.234-350, 2001(2).
  12. E. Lee, K. Park, M. Whang, and K. Min, "Measuring the degree of eyestrain caused by watching LCD and PDP devices," Int. J. of Industrial Ergonomics, Vol.39, Issue.5, pp.798-806, 2009(9).
  13. 배민경, 장운수, 조지혜, 김치중, 이의철, "정확한 동공 검출 및 분석을 통한 감성 특징 추출 및 시각화 방법", 제25회 신호처리합동학술대회, 성균관대학교, 2012(9).
  14. J. Daugman, "High confidence visual recognition of personals by a test of statistical independence," IEEE Trans. Pattern Anal. Machine Intell., Vol.15, Issue.11, pp.1148-1160, 1993(11).
  15. J. Daugman, "New Methods in Iris Recognition," IEEE Trans. On Systems, Man, and Cybermetics, PartB: Cybermetics, Vol.37, Issue.5, pp.1167-1175, 2007(10).
  16. T. Tan, Z. He, and Z. Sun, "Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition," Image and Vision Computiong, Vol.28, Issue.2, pp.223-230, 2010(2).
  17. E. Lee, J. Lee, and K. Park, "Experimental Investigations of Pupil Accommodation Factors," Investigative Ophthalmology & Visual Science, Vol.52, No.9, pp.6478-6485, 2011(7).
  18. C. Basch, "Focus Group Interview:An Underutilized Research Technique for Improving Theory and Practice in Health Education," Health education & Behavior, Vol.14, No.4, pp.411-448, 1987(12).
  19. B. Moser, G. Stevens, and C. Watts, "The two-sample test versus Satterthwaite's approximate f test. Communications in Statistics," Theory and Methods, Vol.18, Issue.11, pp.3963-3975, 1989(5).