Abstract
In the paper, we investigate the problem of an aggregation of classifiers based on numerical and linguistic values of facial features. In the literature, there are many reports of the studies discussing the aggregation or information fusion, however in the situation when the specific classification methods utilize numeric, not linguistic values. Here, we examine the well-known methods (Eigenfaces, Fisherfaces, LBP, MB-LBP, CCBLD) supported by the linguistic values of the measurable facial segments. The detailed results of experiments on the MUCT and PUT facial databases show which of the common aggregation functions and methods have a significant potential to improve the classification process.