A method to combine visual and infrared face image verification systems

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 templates are then compared for decision scores generation. Finally the scores from the visual and infrared face image verification systems are fused by an error rate minimization formulation. Our empirical observation shows encouraging results regarding the effectiveness of the fusion.