Real-time Face Detection and Recognition using Classifier Based on Rectangular Feature and AdaBoost

사각형 특징 기반 분류기와 AdaBoost 를 이용한 실시간 얼굴 검출 및 인식

Face recognition technologies using PCA(principal component analysis) recognize faces by deciding representative features of faces in the model image, extracting feature vectors from faces in a image and measuring the distance between them and face representation. Given frequent recognition problems associated with the use of point-to-point distance approach, this study adopted the K-nearest neighbor technique(class-to-class) in which a group of face models of the same class is used as recognition unit for the images inputted on a continual input image. This paper proposes a new PCA recognition in which database of faces.