On Fisher vector encoding of binary features for video face recognition

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Black-Box vs. White-Box: Understanding Their Advantages and Weaknesses From a Practical Point of View (2019, methodology): “One of the most outstanding application areas for the SVMs is biometrics [13], [14], [24]–[28].”
Contrast Pattern-Based Classification for Bot Detection on Twitter (2019, background): “There already exist various understandable classification mechanisms, which have been used for solving real-world applications [19]–[22].”
Toward More Realistic Face Recognition Evaluation Protocols for the YouTube Faces Database (2018, methodology): “Specifically, we tested the Video Fisher Vector Faces (VF(2)) descriptor[12] that encodes SIFT features, and the Binary Video Fisher Vector Faces (BinVF(2)) [10] and the Logistic Binary Video Fisher Vector Faces (LBinVF(2)) [11], which efficiently encode BRIEF descriptors.”