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The data captured by existing standoff biometric systems typically has lower biometric recognition performance than their close range counterparts due to imaging challenges, pose challenges, and other factors. To assist in overcoming these limitations systems typically perform in a multi-modal capacity such as Honeywell's Combined Face and Iris (CFAIRS) [21] system. While this improves the systems...
3D face modeling from 2D face images is of significant importance for face analysis, animation and recognition. Previous research on this topic mainly focused on 3D face modeling from a single 2D face image; however, a single face image can only provide a limited description of a 3D face. In many applications, for example, law enforcement, multi-view face images are usually captured for a subject...
Correction of uneven illumination in face images has been a task of intense research with its applicability being extensive. Most algorithms look to improve recognition accuracy failing to produce visually good results or viceversa. In this work, we present a data-driven illumination correction algorithm which simultaneously produces visually good results and improves recognition accuracy among faces...
The matching performance of automated face recognition has significantly improved over the past decade. At the same time several challenges remain that significantly affect the deployment of such systems in security applications. In this work, we study the impact of a commonly used face altering technique that has received limited attention in the biometric literature, viz., non-permanent facial makeup...
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