본 논문에서는 다중 특징 결합과 유사도 공간을 이용한 실제적인 온라인 얼굴 검증 시스템을 구현하는 방법을 제안한다. 얼굴 검증에서의 주요 쟁점은 다양한 얼굴 형상 변화의 처리이다. 이러한 변화는 단지 한가지 특징만으로는 해결되기 어렵다. 따라서 얼굴 형상에 있어서의 다양한 변화를 처리하기 위해서 상호보완적인 특징들의 결합이 필요하다. 이러한 관점에서 우리는 다중 주성분 분석과 에지 분포에 기반한 특징 추출 방법을 제안한다. 이러한 특징들은 다수의 간단한 유사도 측정 방법들로 형성된 새로운 intra-person/extra-person 유사도 공간으로 사상되고, 최종적으로 Support Vector Machine에 의해 평가된다. 실제적인 대용량 데이타베이스로 실험한 결과, equal error rate 0.029의 결과를 나타내었고, 이는 많은 실제 응용제품에도 충분히 적용 가능한 수준이다.
KSP Keywords
Support vector, equal error rate
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