디스플레이 장치 조정을 통한 실물과 디스플레이 출력 얼굴 동영상의 얼굴 인식 성능 유사성 향상
Similarity Enhancement of Face Recognition Performance between Real Faces and Facial Videos through Adjustment of a Display Device
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초록
얼굴인식 기술은 다른 생체인식 기술과 달리 사용자의 특별한 동작이나 요구없이 비접촉식으로 자연스럽게 식별할 수 있는 기술이다. 최근 얼굴인식 기술의 발전으로 보안 시스템, 지능형 로봇 등 다양한 분야에 적용되고 있으나, 실 환경에서 제품의 얼굴인식 성능이 사용자의 기대에 미치지 못해 상용화에 어려움을 겪고 있다. 제품의 얼굴인식 성능은 실 환경에서 조명과 사용자의 포즈, 표정 변화 등에 영향을 받으며, 이로 인해 실험실 환경에서 알고리즘 성능과 차이가 발생한다. 알고리즘 성능과의 차이를 줄이고자 알고리즘, 인간모형, 고화질의 사진을 이용한 다양한 제품기반 성능평가 방법이 제안되었으나, 실 환경을 모사하기에는 한계가 있었다. 최근에는 디스플레이 장치와 캡처 장비의 발전으로 실제 사람 얼굴을 대신하여 디스플레이 장치로부터 출력되는 고화질의 얼굴 동영상을 이용한 성능평가 방법이 제안되었다. 본 논문에서는 디스플레이 장치의 감마 조정을 통해 인식 성능 측면에서 실물과 디스플레이 장치 출력 얼굴 동영상의 유사성을 향상시키고자 한다.
Abstract
As face recognition technology, unlike other biometric methods, is more direct, user friendly, and convenient, it is applicable to many areas including security systems and service robot. However, the performance of face recognition systems in a real service environment does not always satisfy the expectations of users, because the performance of face recognition systems is influenced by the user's pose, expression change and lighting in the real environment. So, there is the performance gap between a real service and laboratory environment. To reduce the gap, there are many approaches using such as an algorithm, a mannequin and a high-definition photograph. Unfortunately, it has a limitation to construct a test environment in which the various situations faced by a user and an face recognition system are created similar to those encountered in real environments. Recently, with the development of the display device and capture devices, the performance evaluation method using the high-quality face video output from the display device in place of the actual human face to are proposed. In this paper, we demonstrate the similarity enhancement of face recognition performance between real face and facial videos from display device through gamma adjustment.
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