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| Performance Evaluation System in Open Set Face Recognition |
| LIANG Yi-Cong, DING Xiao-Qing, FANG Chi |
| Center for Intelligent Image and Document Information Processing, Department of Electronic Engineering, Tsinghua University, Beijing 100084 |
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Abstract A performance evaluation system is built for the open set face recognition task. The system consists of two parts: the quality evaluation for training set and the performance evaluation for classification result of test samples. For the former, Bhattacharyya distance is used to approximate the Bayesian error rate, and the particularity of open set problems that sample pairs do not obey the independent identical distribution assumptions is taken into account. The quality evaluation functions of the training set are obtained in both Gaussian or non-Gaussian distribution assumptions, and in Gaussian case this function has a closed form. For the latter, the distribution densities of the nearby positive and negative sample pairs are considered to measure the reliability of the similarity score given by a classifier. Therefore, the previous studies which are lacking of such measurements are complemented. The results in this paper are validated by experiments on multiple face databases.
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Received: 21 February 2013
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2014, Vol. 27 
