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

대한전자공학회 (The Institute of Electronics and Information Engineers)
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복잡한 배경에서 계층적 주목 연산자를 이용한 다중 얼굴 검출

Multi-face Detection from Complex Background Using Hierarchical Attention Operators

  • 이재근 (주식회사 디보스) ;
  • 김복만 (경북대학교 전자전기컴퓨터학부) ;
  • 서경석 (경북대학교 전자전기컴퓨터학부) ;
  • 최흥문 (경북대학교 전자전기컴퓨터학부)
  • 발행 : 2004.11.01
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⟨ 이전 논문 다음 논문 ⟩

초록

본 논문에서는 단일 문맥자유 주목 연산자 (context-free attention operator)만을 계층적으로 적용하여 복잡배경의 인물 영상으로부터 여러 얼굴을 효과적으로 동시 검출하는 알고리즘을 제안하였다. 입력 영상을 피라미드 구조로 변환하고, 잡음에 강건한 주목 연산자를 전역적으로 적용하여 먼저 고속으로 얼굴이 존재할 후보영역들을 찾고, 다시 이 영역들에 국한하여 지역적인 주목 연산자를 적용하여 얼굴이 갖는 특징을 확인함으로써 얼굴임을 검증하였다. 복잡 배경 속에 여러 얼굴을 포함하는 여러 가지 인물 영상 데이터베이스에 대해 제안한 알고리즘을 적용한 결과 93.5%의 검출율을 얻을 수 있었다.

An efficient multi face detection technique is proposed based on hierarchical context-free attention operators in which multiple faces are efficiently detected from a noisy and complex background. A noise-tolerant generalized symmetry transform (NTSGT) is applied hierarchically, as a context free attention operator, to the input pyramidal image for the high speed global location of the regions of face candidates (ROFCs) with a single mask. For the face verification, local NTGST is applied within each ROFC to confirm the existence of the detailed facial features. First, by globally applying NTGST which introduces the average pyramid method and focusing to the input image with complex background, ROFCs with recognizable resolution are detected robustly. Morphological operations are applied only to the each detected ROFCs to emphasize the facial features like eyes and lips. Then, eyes are detected by locally appling NTGST to the ROFCs and only faces are detected by verifying the existence of the geometrical features of the faces relatively to the location of eyes. The experimental results show that the proposed method can efficiently detect multiple faces from a noisy or complex background with 93.5% detection rate.

키워드

참고문헌

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