Abstract
AbstractWe 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.KeywordsFace RecognitionRecognition RateFace ImageImage PairThermal ImageThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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