Jeffrey R. Paone

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The biometric menagerie is useful in identifying the troublesome users within a biometric recognition system. In order to maximize the benefits of the menagerie classifications, it is imperative that the classifications remain constant for each subject. Irises present one of the unique scenarios for classification since each iris represents the same subject(More)
Biometric identification systems must be able to distin­ guish between individuals even in situations where the bio­ metric signature may be similar, such as in the case of iden­ tical twins. This paper presents experiments done in facial recognition using data from a set of images of twins. This work establishes the current state of facial recognition in(More)
Facial recognition algorithms should be able to operate even when similar-looking individuals are encountered, or even in the extreme case of identical twins. An experimental data set comprised of 17486 images from 126 pairs of identical twins (252 subjects) collected on the same day and 6864 images from 120 pairs of identical twins (240 subjects) with(More)
The performance of face recognition algorithms is affected both by external factors and internal subject characteristics [1]. Reliably identifYing these factors and understanding their behavior on performance can potentially serve two important goals to predict the performance of the algorithms at novel deployment sites and to design appropriate acquisition(More)
Keeping a driver focused on the road is one of the most critical steps in insuring the safe operation of a vehicle. The Strategic Highway Research Program 2 (SHRP2) has over 3,100 recorded videos of volunteer drivers during a period of 2 years. This extensive naturalistic driving study (NDS) contains over one million hours of video and associated data that(More)
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