Издательство — Речевые технологии — Выпуск №3/2020

Abstract. This paper explores an approach to constructing classes of various movements of a person’s hands while showing gestures and methods for recognizing them. The localization of the hand relative to the body, the direction of movement of the hands and the orientation of the palm are taken as the main properties while showing gestures. To build classes, the use of an ontological model of the subject area, focused on the problems of recognizing sign language is proposed. To analyze the data and build the ontological model, about a thousand gestures that characterize the possible variations of gestures in the form of their demonstration were selected. As a result of the research, more than two hundred different classes have been identifed for which various methods and recognition algorithms have been developed taking into account the specifc features of the classes. Approaches to the detection and recognition of gestures during the implementation of intelligent human-machine interface technology are considered. A new algorithm based on the Bernsen method and morphological structuring and correlation analysis is proposed. Based on the algorithm, a system was created and an experiment was carried out. The experimental results showed the effectiveness of the proposed algorithm and can be used to recognize other types of classes proposed in the classifcation by modifying the proposed algorithm, that is, using various methods for processing matrices.

Keywords: gestures recognition, human-machine interface, Viola-Jones detector, correlation analysis, sign language translation, the Bernsen method.