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- W2734232040 abstract "A comprehensive nonparametric statistical learning framework, called LPiTrack, is introduced for large-scale eye-movement pattern discovery. The foundation of our data-compression scheme is based on a new Karhunen–Loéve-type representation of the stochastic process in Hilbert space by specially designed orthonormal polynomial expansions. We apply this novel nonlinear transformation-based statistical data-processing algorithm to extract temporal-spatial-static characteristics from eye-movement trajectory data in an automated, robust way for biometric authentication. This is a significant step towards designing a next-generation gaze-based biometric identification system. We elucidate the essential components of our algorithm through data from the second Eye Movements Verification and Identification Competition, organized as a part of the 2014 International Joint Conference on Biometrics." @default.
- W2734232040 created "2017-07-14" @default.
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- W2734232040 date "2017-06-29" @default.
- W2734232040 modified "2023-09-27" @default.
- W2734232040 title "LPiTrack: Eye movement pattern recognition algorithm and application to biometric identification" @default.
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- W2734232040 doi "https://doi.org/10.1007/s10994-017-5649-1" @default.
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