title: Thresholded two-phase test sample representation for outlier rejection in biological recognition.
abstract: 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.
authors.affiliation: Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin 150001, China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Wu
authors.forename: Ning
authors.initials: N
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D016208:Databases, Factual; D005145:Face / Q000502:physiology*; D005189:False Positive Reactions; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D016247:Information Storage and Retrieval; D016014:Linear Models; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D012372:ROC Curve; D021641:Recognition, Psychology; D015203:Reproducibility of Results
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