The GBU challenge problem consists of three partitions which are called the Good (easy to match), the Bad (average matching difficulty) and the Ugly (difficult ...

Predicting Good, Bad and Ugly Match Pairs. Gaurav Aggarwal, Soma Biswas, Patrick J. Flynn and Kevin W. Bowyer. Department of Computer Science and Engineering.

A Bayesian model for predicting face recognition performance using image quality · Computer Science. IEEE International Joint Conference on Biometrics · 2014.

The GBU challenge problem consists of three partitions which are called the Good (easy to match), the Bad (average matching difficulty) and the Ugly (difficult ...

For the Good partition, the verification rate at a FAR of 1/1000 for all four cases is better than all cases in the Bad partition.

The Good partition consists of pairs of face images of the same person that are easy to match; the Bad partition contains pairs of face images of a person that ...

The Good, the Bad, & the Ugly Face Challenge Problem was created to encourage the development of algorithms that are robust to recognition across changes ...

The Good, the Bad, and the Ugly consists of three partitions. The Good partition contains pairs of images that are considered easy to recognize. The base ...

Jul 2, 2014 · Aggarwal et al.[82] show that good, bad, ugly pairs can be predicted by using partial least square regression between image-based features ( ...

It provides three protocols that mainly evaluate different illumination conditions called Good, Bad, and Ugly, where Ugly is the most difficult protocol, while ...