Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin 150001, China.
Comput Math Methods Med. 2013;2013:248380. doi: 10.1155/2013/248380. Epub 2013 Mar 11.
The two-phase test sample representation (TPTSR) was proposed as a useful classifier for face recognition. However, the TPTSR method is not able to reject the impostor, so it should be modified for real-world applications. This paper introduces a thresholded TPTSR (T-TPTSR) method for complex object recognition with outliers, and two criteria for assessing the performance of outlier rejection and member classification are defined. The performance of the T-TPTSR method is compared with the modified global representation, PCA and LDA methods, respectively. The results show that the T-TPTSR method achieves the best performance among them according to the two criteria.
两阶段测试样本表示（TPTSR）被提出作为人脸识别的一种有用的分类器。然而，TPTSR 方法不能够拒绝冒名顶替者，因此它应该为实际应用而修改。本文提出了一种用于具有离群值的复杂对象识别的门限 TPTSR（T-TPTSR）方法，并定义了两个用于评估离群值拒绝和成员分类性能的标准。将 T-TPTSR 方法的性能与修改后的全局表示、PCA 和 LDA 方法进行了比较。结果表明，根据这两个标准，T-TPTSR 方法的性能最佳。
