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

The Institute of Electronics and Information Engineers (대한전자공학회)
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A 3D Face Reconstruction Method Robust to Errors of Automatic Facial Feature Point Extraction

얼굴 특징점 자동 추출 오류에 강인한 3차원 얼굴 복원 방법

  • Lee, Youn-Joo (School of Electrical and Electronic Engineering, Yonsei University, Biometrics Engineering Research Center) ;
  • Lee, Sung-Joo (School of Electrical and Electronic Engineering, Yonsei University, Biometrics Engineering Research Center) ;
  • Park, Kang-Ryoung (Division of Electronics and Electrical Engineering, Dongguk University, Biometrics Engineering Research Center) ;
  • Kim, Jai-Hie (School of Electrical and Electronic Engineering, Yonsei University, Biometrics Engineering Research Center)
  • 이연주 (연세대학교 전기전자공학과, 생체인식 연구센터) ;
  • 이성주 (연세대학교 전기전자공학과, 생체인식 연구센터) ;
  • 박강령 (동국대학교 전자전기공학부 생체인식연구센터) ;
  • 김재희 (연세대학교 전기전자공학과, 생체인식 연구센터)
  • Received : 2010.11.15
  • Accepted : 2010.12.19
  • Published : 2011.01.25
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Abstract

A widely used single image-based 3D face reconstruction method, 3D morphable shape model, reconstructs an accurate 3D facial shape when 2D facial feature points are correctly extracted from an input face image. However, in the case that a user's cooperation is not available such as a real-time 3D face reconstruction system, this method can be vulnerable to the errors of automatic facial feature point extraction. In order to solve this problem, we automatically classify extracted facial feature points into two groups, erroneous and correct ones, and then reconstruct a 3D facial shape by using only the correctly extracted facial feature points. The experimental results showed that the 3D reconstruction performance of the proposed method was remarkably improved compared to that of the previous method which does not consider the errors of automatic facial feature point extraction.

최근에 널리 사용되고 있는 단일 영상 기반의 3차원 얼굴 복원 방법인 변형 가능한 3차원 얼굴 형상 모델(3D morphable shape model)은 입력 영상으로부터 2차원 얼굴 특징점들을 정확하게 추출할 경우, 입력 얼굴과 유사한 3차원 얼굴 형상을 생성할 수 있다. 그러나 실시간 3차원 얼굴 복원 시스템과 같이 사용자의 협조가 불가능한 경우에는 자동으로 얼굴 특징점들을 추출해야 하기 때문에, 특징점 추출 오류가 발생하여 정확한 3차원 얼굴 형상을 생성하기 어려운 문제가 있다. 이러한 문제를 해결하기 위해서, 본 논문에서는 특징점 추출 시 오추출 특징점과 정추출 특징점을 자동으로 분류하고, 정추출 특징점들만을 이용하여 3차원 얼굴을 복원하는 방법을 제안하였다. 실험결과에서는 특징점 자동 추출 오류를 고려하지 않은 기존 방법과 비교한 결과, 제안방법의 3차원 얼굴 복원 성능이 크게 향상되었음을 확인하였다.

Keywords

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