Byung-Gue Choi

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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(More)
This paper presents a score level fusion of visual and infrared face image verification systems. A high dimensional random projection is first applied to the raw visual and infrared face images to extract useful information relevant to each identity. This is followed by a dimension reduction using eigenfeature regularization and extraction. The resultant(More)
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