Graduate mentor's supervisor: Prof. Ana Crissan
This project aims to enhance a research platform for creating and analyzing interactive, web-based data visualization studies by adding an eye-tracking analysis toolkit. Eye-tracking can help researchers understand where users focus, how they analyze problems, and how they make decisions while interacting with websites and data visualizations. However, analyzing gaze data often requires expensive commercial software. This project aims to address that challenge by developing an open and accessible toolkit for analyzing common gaze measures from recorded user studies. By simplifying gaze analysis, the toolkit could support the development of adaptive visualization systems that respond to users’ needs and difficulties.
The toolkit will extend ReVISitBench, a platform for creating and analyzing interactive, web-based visualization studies. We have already completed an initial integration of the Tobii Pro SDK, and the current system supports basic gaze-coordinate tracking and heatmap vis. Students will build on this foundation by integrating additional SDK functions for commonly used gaze measures, such as AOI fixations, saccades, revisits, and blink metrics, and by developing richer visualizations for interpreting participant gaze behaviour.
This project is well-suited for students interested in human-computer interaction, data visualization, web development, and multimodal research methods. No prior research or eye-tracking experience is required, and students with basic programming experience and knowledge of GitHub are welcome. At least one team member should be familiar with the React framework and Python and be comfortable reading and modifying an existing codebase.
Students will work in a team of three to four, with complementary responsibilities. Two students may focus on reviewing and organizing related literature, identifying gaps in existing gaze-analysis tools, and translating those findings into system requirements. One or two students may focus on integrating existing Python functions from the Tobii Pro SDK into the platform and connecting the analysis results to the React interface. Students will not be expected to develop eye-tracking algorithms from scratch. During the term, the team will study existing approaches, define requirements, and build a working gaze-analysis toolkit using Tobii Pro SDK functions. Longer-term goals include evaluating the toolkit with users, refining the interface and design guidelines, and contributing to a research paper.