Open Set Face Recognition
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Introduction |
Open set recognition is significant for the applications of face recognition system. Prior to closed set recognition, open set recognition makes no assumption that all probes (test exemplars) have been registered on the gallery set (known identities database). An open set face recognition system has to decide whether the probes are known identities or imposters. Imposters are rejected, while genuine identities are accepted and then to be classified. Open set recognition is more practical for applications that usually confronts with unknown people. However, open set recognition is a definitely challenge for modern pattern recognition. Compared with closed set recognition, open set recognition system has to deal with two more issues of rejecting genuine identities or accepting imposters respectively. It is hard to deal with these two issues at the same time for their contradictory characteristics. In this paper, we propose a
novel method to address open set face recognition problem. It extends
the general Adaboost face recognition (GAFR) method used for closed set
task, and makes it suitable for open set task. Because |
Two Stage Recognition Structure |
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Comparison with GAFR | |
(a) |
(b) |
Similarity distribution of positive and negative pairs using: (a) GAFR method, (b) our method. |
Reference |
[1] D.Liu, J. Dai and J. Su.
Open Set Face Recognition using Adaboost and Genetric Transformation.
TR-SJTU-RCIR, October 2008. |