@inproceedings{e6391dc21d28476c9e34eeac8022bf5c,
title = "Fusing horizontal and vertical components of face images for identity verification",
abstract = "This paper presents an empirical investigation of two sparse random projections which correspond to extraction of vertical and horizontal features from a face image for identity verification. In order to enhance the performance of each projection, the matching scores of both directional features are fused via a Total Error Rate minimization. The BERC face database is used for evaluating the effectiveness of the proposed method. Our empirical results show that the proposed vertical projection outperforms the commonly used PCA and a Random Projection algorithm in terms of the Equal Error Rate (EER) measure. The result of fusion shows an even better EER performance than that from each individual projection.",
keywords = "Local feature extraction, Random projection, Scores fusion, Total error rate",
author = "Oh, \{Beom Seok\} and Choi, \{Byung Gue\} and Toh, \{Kar Ann\}",
year = "2009",
doi = "10.1109/ICIEA.2009.5138286",
language = "English",
isbn = "9781424428007",
series = "2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009",
pages = "651--655",
booktitle = "2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009",
note = "2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009 ; Conference date: 25-05-2009 Through 27-05-2009",
}