Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Face Detection Using Support Vector Domain Description in Color Images

컬러 영상에서 Support Vector Domain Description을 이용한 얼굴 검출

  • Seo Jin (Dept. of Electronics & Computer Engineering, Korea University) ;
  • Ko Hanseok (Dept. of Electronics & Computer Engineering, Korea University)
  • 서진 (고려대학교 전자컴퓨터공학과) ;
  • 고한석 (고려대학교 전자컴퓨터공학과)
  • Published : 2005.01.01
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Abstract

In this paper, we present a face detection system using the Support Vector Domain Description (SVDD) in color images. Conventional face detection algorithms require a training procedure using both face and non-face images. In SVDD however we employ only face images for training. We can detect faces in color images from the radius and center pairs of SVDD. We also use Entropic Threshold for extracting the facial feature and sliding window for improved performance while saving processing time. The experimental results indicate the effectiveness and efficiency of the proposed algorithm compared to conventional PCA (Principal Component Analysis)-based methods.

본 논문에서는 컬러 영상에서 Support Vector Domain Description (SVDD)를 이용한 얼굴 검출 방법을 제안한다. 기존의 훈련을 통한 얼굴 검출 방법은 얼굴 영상과 얼굴이 아닌 영상을 모두 사용해야 한다. 그러나, SVDD를 이용한 얼굴 검출은 단지 훈련을 위해 얼굴 영상만이 사용된다. SVDD의 훈련을 통해 나오는 값인 반지름과 중심 좌표를 통해 얼굴을 검출한다. 또한, 엔트로피를 이용한 임계값 추출 방법(Entropic Threshold)을 통해 얼굴 특징을 추출하고, 슬라이딩 윈도우(sliding window)기법을 통해 성능을 개선한다. 주성분 분석(Principle Component Analysis) 과 SVDD를 이용한 얼굴 검출 방법의 비교 실험을 통해 본 논문이 제안한 방법의 효율성을 확인한다.

Keywords

References

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