Automatic identification of experts in visual arts: The use of transitions between regions of interest in the image

摘要

The aim of this paper is to investigate the use of oculography signals for the recognition of experts in visual arts. We focused our attention on the number of sight transitions between characteristic image areas (ROIs). In the experiments we used oculographic data recorded at the Department of Experimental Psychology at the Catholic University of Lublin for 29 images and 34 users. The EM method was used to determine the ROIs, and the BIC criterion for determining the optimal number of clusters. The selected values of the matrix of transitions were used for learning and testing of the classifier. Very rigorous testing of the proposed algorithm was carried out approaching the actual operating conditions of the expert system. The presented results indicate that for some images there is a chance of identifying experts in the field of visual arts using transitions as oculographic features.