The dynamic time warping algorithm (DTW) is designed to compare two time series by measuring the distance between them. DTW is widely used in medicine, speech recognition, financial market and gaze trajectories analysis. Considering the classic version of DTW, as well as its various modifications, it was found that in the tasks of analyzing the distance between gaze trajectories, they are not able to correctly take into account the duration of its fixations on visual stimuli. The problem has not attracted much attention so far, although its solution will improve the accuracy and interpretation of the results of many experimental studies, since assessing the time of visual focus on objects is an important factor in visual analysis. Hence the need to adapt DTW for such tasks. The goal of this work is to adapt the classic DTW to the problem of finding the distance between two time series with periods of low variability of values. During the demonstration of the developed algorithm, it was proven that the effect of a given minimum threshold of fixation duration on the result is significant. The proposed adaptation of DTW will improve the quality of visual data analysis and can be applied to understanding the mechanisms of human perception and decision-making in various fields of activity, such as psychology and marketing, as well as to developing effective methods for testing interfaces.

Keywords: dynamic time warping algorithm, eye tracking, time series, gaze trajectory, gaze fixation duration

The term "oculography" (eye tracking) describes a technological method used to record eye movements in real time. This technique allows researchers to analyze the focus of subjects' attention on various interface elements. Color is a powerful tool for attracting attention. Understanding which colors first attract attention allows marketers to correctly place accents on visual stimuli, such as advertising materials that feature clothing of different colors, in order to improve the experience of interaction of a potential consumer with this content. The purpose of this work is to determine the effect of the black color of clothing on the priority of human attention. To achieve this goal, experiments were conducted in which the gaze of subjects was tracked using a webcam while they studied an experimental image. The analysis of the final experimental data obtained using the adapted velocity threshold identification algorithm showed a high attention priority for the black color of clothing. In 87.5% of cases, attention was paid to it first, while the gender of the subject did not play a significant role in this perception. The obtained results can help in the development of research aimed at improving the efficiency of information perception.

Keywords: oculography, velocity threshold identification algorithm, eye tracking technology, attention priority, region of interest, time to first fixation, advertising, clothing, color

Eye tracking (oculography) is a technology that allows recording the direction of human gaze on a visual stimulus. It’s application can provide researchers with valuable data on which elements of the environment are most attractive in various contexts, in areas such as marketing, psychology, etc. The aim of this work is to identify the pattern of human attention distribution on visual stimulus objects of different sizes using eye tracking technology. A webcam was used to record the subjects’ gaze movements while they were studying experimental images. The results of the experiments showed that larger objects in visual stimuli receive higher attention priority than smaller objects. This observation is true for both human-created works and images created by artificial intelligence (Kandinsky 3.1 is used in this study). The obtained results of the study will improve our understanding of how people perceive visual information, which can contribute to the creation of more effective approaches to interface development.

Keywords: eye tracking technology, attention priority, region of interest, number of eye gaze registrations, artificial intelligence, Vincent Van Gogh