Linguistic Descriptors in Face Recognition

In this study, we propose linguistic descriptors-based approach to the problem of face identification realized by both humans and computers. This approach is motivated by an evident observation that linguistic descriptors offer an ability to formalize and exploit important pieces of knowledge describing human's face. These entities are used by people in face recognition and could be found of importance in building machine-oriented recognition schemes. Moreover, evident humans' abilities to recognize other individuals can be incorporated into computational face recognition problems as an invaluable vehicle improving recognition rate of machine-oriented classifiers. Specifically, we propose an application of analytic hierarchy process to determine linguistic values of facial features. The experts' assessments of faces in terms of such attributes support coping with uncertainty captured through experts' decisions result in a set of useful assuring the desired property of inter-class similarities and between-class differences among faces. It is worth noting that the method presented in this study can be easily applied to any other classification problem with the presence of experts.