The KIPS Transactions:PartB (정보처리학회논문지B)

Korea Information Processing Society (한국정보처리학회)
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A Real-Time Face Detection/Tracking Methodology Using Haar-wavelets and Skin Color

Haar 웨이블릿 특징과 피부색 정보를 이용한 실시간 얼굴 검출 및 추적 방법

  • 박영경 (성균관대학교 정보통신공학부) ;
  • 서해종 (성균관대학교 정보통신공학부) ;
  • 민경원 (전자부품연구원 디지털미디어 연구센터) ;
  • 김중규 (성균관대학교 정보통신공학부)
  • Published : 2006.06.01
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Abstract

In this paper, we propose a real-time face detection/tracking methodology with Haar wavelets and skin color. The proposed method boosts face detection and face tracking performance by combining skin color and Haar wavelets in an efficient way. The proposed method resolves the problem such as rotation and occlusion due to the characteristic of the condensation algorithm based on sampling despite it uses same features in both detection and tracking. In particular, it can be applied to a variety of applications such as face recognition and facial expression recognition which need an exact position and size of face since it not only keeps track of the position of a face, but also covers the size variation. Our test results show that our method performs well even in a complex background, a scene with varying face orientation and so on.

본 논문은 Haar 웨이블릿 특징과 피부색 정보를 이용한 실시간 얼굴 검출 및 추적 방법을 제안한다. 검출과 추적이 각기 다른 특징들을 이용해 이루어졌던 기존 방법과는 달리 본 논문에서는 피부색 정보와 Haar 웨이블릿 특징을 검출과 추적에 동시에 이용하고 두 특징들을 효과적으로 융합함으로써 빠르고 강인한 추적을 가능하게 한다. 제안된 방법은 검출과 추적에 동일한 특징을 이용함에도 불구하고 표본화에 기반을 둔 Condensation 알고리즘의 특징으로 인해 검출 방법만을 적용했을 때 검출하지 못하는 얼굴의 회전이나 가려짐 등의 문제를 효과적으로 해결한다. 특히, 얼굴의 위치와 함께 크기 변화를 효과적으로 추적하기 때문에 얼굴의 위치 및 크기를 정확하게 알아야 하는 얼굴 인식이나 표정인식 등의 다양한 어플리케이션에 이용되기에 용이하다. 제안된 방법은 복잡한 배경 및 다양한 얼굴 자세 등의 변화에 대한 테스트를 통해 효율성을 검증한다.

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