Abstract
In this study, we present a new approach to the face retrieval and face classification problem, which exploits available expert's knowledge and introduces a novel way of describing facial features. These features are described by manually assigned weights corresponding to membership grades with respect to the linguistic descriptors such as short, medium, or long. In the series of experiments, we also use weights produced by the Analytic Hierarchy Process aimed at producing saliences of facial cues. We identify a group of the most essential facial features.