적응적 얼굴 검출기와 칼만 필터를 이용한 실시간 얼굴 추적 시스템

• 영문명: Real-Time Face Tracking System using Adaptive Face Detector and Kalman Filter
• 발행기관: 한국IT서비스학회
• 저자명: 김종호(Jong Ho Kim) 김상균(Sang-Kyoon Kim) 신범주(Bum Joo Shin)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제6권 제3호, 241~249쪽, 전체 9쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2007.12.30

영문 초록

  This paper describes a real-time face tracking system using effective detector and Kalman filter. In the proposed system, an image is separated into a background and an object using a real-time updated face color for effective face detection. The face features are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted using Principal Component Analysis (PCA), and interpreted principal components are used for Support Vector Machine (SVM) that classifies the faces and non-faces. The moving face is traced with Kalman filter, which uses the static information of the detected faces and the dynamic information of changes between previous and current frames. The proposed system sets up an initial skin color and updates a region of a skin color through a moving skin color in a real time. It is possible to remove a background which has a similar color with a skin through updating a skin color in a real time. Also, as reducing a potential-face region using a skin color, the performance is increased up to 50% when comparing to the case of extracting features from a whole region.

목차

Abstract
1. 서론
2. 얼굴 추적 시스템의 전체 구성
3. 적응적 피부색 검출
4. 얼굴 검출기 구성
5. 칼만 필터를 이용한 얼굴추적
6. 실험 및 분석
7. 결론 및 향후 연구
참고문헌
저자소개

키워드

Adaptive Skin Detection Face Tracking Face Detection SVM Kalman Filter