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Person re-identification on image sets in which each image is taken from a different angle and lighting condition is a very challenging task. This task becomes even more difficult when images are low resolution and carrying image compression artifacts. The accuracy of the existing re- identification techniques are relatively low on the challenging evaluation grounds such as VIPeR and iLIDS image datasets...
We propose a quick and widely applicable approach for converting biometric identification match scores to probabilistic confidence scores, resulting in increased discrimination accuracy. This approach builds on a confidence scoring approach for Binomial distributions resulting from Hamming distances (commonly used in iris recognition). We derive a Gaussian confidence scoring approach that is three...
In order to advance face recognition research, algorithm performance has to be measured and compared using a range of metrics and operating characteristics. While public challenges such as the NIST-sponsored FERET, FRVT, FRGC, and MBGC are helpful to gauge comparative performance and improvement for a particular scenario, they typically are not sufficient to fully characterise the strengths and weaknesses...
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