title: Image Generation Using Bidirectional Integral Features for Face Recognition with a Single Sample per Person.
abstract: In face recognition, most appearance-based methods require several images of each person to construct the feature space for recognition. However, in the real world it is difficult to collect multiple images per person, and in many cases there is only a single sample per person (SSPP). In this paper, we propose a method to generate new images with various illuminations from a single image taken under frontal illumination. Motivated by the integral image, which was developed for face detection, we extract the bidirectional integral feature (BIF) to obtain the characteristics of the illumination condition at the time of the picture being taken. The experimental results for various face databases show that the proposed method results in improved recognition performance under illumination variation.
authors.affiliation: Department of Computer Science and Engineering, Dankook University, 126, Jukjeon-dong, Suji-gu, Yongin-si, Gyeonggi-do, 448-701, Korea.
authors.forename: Yonggeol
authors.initials: Y
authors.lastname: Lee
authors.affiliation: Division of Electrical Engineering, Hanyang University, 55 Hanyangdaehak-ro, Sangnok-gu, Ansan-si, Gyeonggi-do, 426-791, Korea.
authors.forename: Minsik
authors.initials: M
authors.lastname: Lee
authors.affiliation: Department of Computer Science and Engineering, Dankook University, 126, Jukjeon-dong, Suji-gu, Yongin-si, Gyeonggi-do, 448-701, Korea.
authors.forename: Sang-Il
authors.initials: SI
authors.lastname: Choi
mesh_terms: D000465:Algorithms; D019992:Databases as Topic; D005145:Face / Q000033:anatomy & histology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*