Abstract
In this paper, we discuss an application of the linguistic descriptions obtained directly from experts' and treated as the votes when characterizing facial images to carry out face classification. Despite various automated face recognition techniques, the expert's opinion plays a pivotal role in making classification decisions when recognizing faces, say in problems of suspect identification. Here, we analyze the impact of critical factors (e.g., a number of experts, voting schemes, distance functions) and their impact on the performance of classification schemes. The well-established Analytic Hierarchy Process (AHP) is used to quantify importance of linguistic descriptors in the process of face recognition by humans. As a result we produce realistic weights improving the accuracy of classification. Experimental results are presented including a number of parametric studies.