Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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A Study on the Performance Enhancement of Face Detection using SVM

SVM을 이용한 얼굴 검출 성능 향상에 대한 연구

  • 이지근 (원광대학교 컴퓨터공학과) ;
  • 정성태 (원광대학교 전기전자 및 정보공학부)
  • Published : 2005.04.01
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Abstract

This paper proposes a method which improves the performance of face detection by using SVM(Support Vector Machine). first, it finds face region candidates by using AdaBoost based object detection method which selects a small number of critical features from a larger set. Next it classifies if the candidate is a face or non-face by using SVM(Support Vector Machine). Experimental results shows that the proposed method improve accuracy of face detection in comparison with existing method.

본 논문에서는 SVM(Support Vector Machine)을 이용하여 얼굴 검출 성능을 향상시키는 방법을 제안한다. 본 논문에서는 먼저 영상내의 거대한 특징 집합으로부터 중요한 작은 특징 집합을 선택하는 AdaBoost 기반 객체 검출 방법을 사용하여 얼굴 후보 영역을 검출한다. 그 다음에는 특징 벡터에 대해 SVM 기반 이진분류를 수행하여 후보 영역의 영상이 얼굴인지 아닌지를 판별한다 실험 결과 본문에서 제안한 방법은 기존의 방법에 비하여 얼굴 검출의 정확도를 향상시켰다.

Keywords

References

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