An Open Source Eye Gaze Tracker System to Perform Remote User Testing Evaluations

• Marc G. Capdevila Facens University https://orcid.org/0000-0003-3092-4207
• Karine Aparecida P. Rodrigues Facens University https://orcid.org/0000-0003-4787-7937
• Camila F. Jardim Facens University https://orcid.org/0009-0006-7265-9041
• Renato M. Silva Facens University https://orcid.org/0000-0001-6687-8981

Resumo

Eye gaze trackers are devices designed to identify an individual’s gaze fixation in relation to a screen or another reference point. These tools are widely applied in usability testing as they provide various metrics for studying how people interact with applications. In the past, these tools were expensive and required a controlled environment, as well as trained personnel for proper operation. Although nowadays, new implementations do not require physical hardware to perform these tests, they often rely on license-based models instead of being open source. The objective of this work is to create a standalone system that enables any user to implement a low-cost eye gaze tracker using web technologies. The goal is to facilitate its use in remote and face-to-face studies in a simple way, requiring only a computer and a webcam. We evaluated the impact of three different calibration techniques on the performance of a regression-based prediction algorithm in eye-tracking. In our experiments, the best result of linear regression was obtained with a circular calibration system that uses 160 points. Furthermore, we integrated the system with a web interface and an API, enabling users to record their usability sessions and analyze fixation points through heatmaps.