Eye-gaze-contingent control of the computer interface: Methodology and example for zoom detection

Discrimination of user intent at the computer interface solely from eye gaze can provide a powerful tool, benefiting many applications. An exploratory methodology for discriminating zoom-in, zoom-out, and no-zoom intent was developed for such applications as telerobotics, disability aids, weapons systems, and process control interfaces. Using an eye-tracking system, real-time eye-gaze locations on a display are collected. Using off-line procedures, these data are clustered, using minimum spanning tree representations, and then characterized. The cluster characteristics are fed into a multiple linear discriminant analysis, which attempts to discriminate the zoom-in, zoom-out, and no-zoom conditions. The methodologies, algorithms, and experimental data collection procedure are described, followed by example output from the analysis programs. Although developed specifically for the discrimination of zoom conditions, the methodology has broader potential for discrimination of user intent in other interface operations.