In our work, we discussed various methods of tracking eye movements. The primary purpose of the research was to study tools that are not necessarily intended for scientific use and compare them with standardized and academically renowned methods. In doing so, we focused on accessibility, accuracy, and practical application of methods.
Among the research objectives, we described the selection of eye tracking methods, preparation of test materials, execution of testing, interviewing companies, and analysis and comparison of results. With hypotheses, we explored the possibility of meeting the needs for use within companies with different methods, the comparability of predicting eye movements, and the practicality of various methods in practice.
In the theoretical part, we discussed vision as a key sense, described the processes of visual perception, and focused on defining and developing the field of eye tracking. We described in more detail the methods of tracking eye movements, their advantages and disadvantages. In the second half, we also defined the field of artificial intelligence and its role in the use of technology for tracking eye movements. We continued with a description of the use of methods in practice and the possibilities of data visualization. We concluded with a mention of the need for standardization of data outputs and the importance of personal data security when working with test participants.
In the experimental section, we described the approach to research objectives and their execution. In the results, we presented a comparative analysis, suggestions for use, and provided guidelines for future research.
We concluded that modern eye tracking methods, even if unscientific, are very useful. We found that different methods offer numerous possibilities for use, requiring a thoughtful approach and making compromises for optimal results.
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