Abstract
We report on a system for person identification based on face images. The system uses sequences of visual wavelength intensity and thermal image pairs as input and carries out classification with a set of expert classifiers (such as ANN or SVM) for each input signal separately. The decisions of the classifiers are integrated both over the two signals and over time as new image pairs arrive, using stochastic recursive inference based on Bayes formula. Our experimental results indicate that both recognition and rejection rates are higher than those for the expert classifiers alone.
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Hild, M., Kuzui, R. (2005). Face Recognition Based on Recursive Bayesian Fusion of Multiple Signals and Results from Expert Classifier Sets. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_25
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DOI: https://doi.org/10.1007/11527923_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27887-0
Online ISBN: 978-3-540-31638-1
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