Journal of KIISE:Software and Applications (한국정보과학회논문지:소프트웨어및응용)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Incremental Face Annotation for Open Web Service

개방형 웹 서버스를 위한 증가적 얼굴 어노테이션

  • 최권택 (연세대학교 컴퓨터과학과) ;
  • 변혜란 (연세대학교 컴퓨터과학과)
  • Published : 2009.08.15
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Abstract

Recently, photo sharing and publishing based Social Network Sites(SNSs) are increasingly attracting the attention of academic and industry researches. Unlike the face recognition environment addressed by existing works, face annotation problem under SNSs is differentiated in terms of daily updated images database, a limited number of training set and millions of users. Thus, conventional approach may not deal with these problems. In this paper, we proposed a face annotation method for sharing and publishing photographs that contain faces under a social network service using random projection, non-linear regression and representational state transfer. Our experiments on several databases show that the proposed method records an almost constant execution time with comparable accuracy of the PCA-SVM classifier.

최근 Flickr, Facebook, Cyworld 처럼 사진 공유를 기반으로 하는 소셜 웹 서비스의 성공과 발달로 얼굴 검출/인식 기술을 이러한 서비스에 접목하려는 다양한 시도가 진행되고 있다. 그러나 인식률 향상에만 초점을 맞춘 기존의 일관처리 기반의 연구들은 수백만의 이용자가 수시로 접근하는 서비스에 적용하기 어렵다. 본 논문에서는 시간에 따라 증가하는 거대한 얼굴 영상 데이터베이스를 효과적으로 분류하기 위해 랜덤 사상(Random Projectio, RP) 비선형 회귀(Non-linear Regression) 그리고 REST(REpresen tational State Transfer) 규약을 사용해 새로운 증가적 얼굴 어노테이션 방법을 제안하고자 한다. 다양한 비교실험 결과에서 제안된 방법은 향상된 인식률과 낮은 계산 복잡도 기록했다. 따라서 제안된 방법은 대규모 웹서비스에 적합한 열굴 어노테이션 알고리즘이다.

Keywords

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