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

The Institute of Electronics and Information Engineers (대한전자공학회)
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Sliding Active Camera-based Face Pose Compensation for Enhanced Face Recognition

얼굴 인식률 개선을 위한 선형이동 능동카메라 시스템기반 얼굴포즈 보정 기술

  • Published : 2004.11.01
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Abstract

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user and is able to doface recognition, which is vital for many surveillance-based systems. The advantage of face recognition compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to the decreasing in dimension from image acquisition step and various changes associated with face pose and background. There are many factors that deteriorate performance of face recognition such as thedistance from camera to the face, changes in lighting, pose change, and change of facial expression. In this paper, we implement a new sliding active camera system to prevent various pose variation that influence face recognition performance andacquired frontal face images using PCA and HMM method to improve the face recognition. This proposed face recognition algorithm can be used for intelligent surveillance system and mobile robot system.

최근 지능형 로봇에 대한 관심이 모아지고 있다. 지능형 로봇의 가장 큰 특징은 사용자를 추적, 인식하고 그 결과를 기반으로 상호활동적인 대응을 할 수 있다는 점이다. 얼굴인식이 다른 생채인식과의 비교에서 장점을 가질 수 있는 점은 비 강제성과 비 접촉성을 들 수 있다. 그러나 얼굴인식은 얼굴 취득단계부터 차원의 감소가 발생하고 인식하고자 하는 얼굴 및 주변 환경 변화가 매우 심하기 때문에 다른 생체인식에 비하여 인식률이 낮다. 얼굴인식의 성능을 저하시키는 요인들로는 조명변화, 포즈변화, 표정변화, 카메라와의 거리 등을 들 수 있다. 본 논문에서는 실제 환경에서 얼굴 인식 성능에 가장 많은 영향을 미치는 포즈변화에 대응하기 위하여 새로운 선형이동 능동형 카메라를 개발하여, 정면 얼굴에 근접한 영상을 취득하고 주성분 분석 및 Hidden Markov Model 알고리듬을 이용하여 인식률을 개선하고자 한다. 제한된 방법은 지능형 보안시스템 및 모바일 로봇에 적용하는 것을 목표로 개발 되었지만, 높은 정확도의 얼굴인식을 요구하는 응용분야에 널리 적용할 수가 있다.

Keywords

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