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Robust estimation of biometric data

Kuijper, Guido (2017) Robust estimation of biometric data.

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Abstract:This study presents the design of a robust estimator Ĉ to apply on biometric data analysis involving facial recognition. This functional estimates the covariance matrix of a multivariate Gaussian distribution by seperately estimating the matrix elements. It is first mathematically derived, then classified by means of its efficiency at Gaussian distributions and finally applied to both synthetic and real biometric data. The synthetic experiments show the Ĉ-estimator performs in between the sample covariance and the MCD estimator. The test with the real data shows clear improvement of the robust Ĉ-estimator as it was able to link two faces for which the sample covariance estimator was not able to.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 53 electrotechnology
Programme:Electrical Engineering BSc (56953)
Link to this item:http://purl.utwente.nl/essays/73245
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