New Features for Eye-Tracking Systems: Preliminary Results

Due to their large number of applications, eye-tracking systems have gain attention recently. In this work, we propose 4 new features to support the most used feature by these systems, which is the location (x, y). These features are based on the white areas in the four corners of the sclera; the ratio of the whites area (after segmentation) to the corners area is used as a feature coming from each corner. In order to evaluate the new features, we designed a simple eye-tracking system using a simple webcam, where the users faces and eyes are detected, which allows for extracting the traditional and the new features. The system was evaluated using 10 subjects, who looked at 5 objects on the screen. The experimental results using some machine learning algorithms show that the new features are user dependent, and therefore, they cannot be used (in their current format) for a multiuser eye-tracking system. However, the new features might be used to support the traditional features for a better single-user eye-tracking system, where the accuracy results were in the range of 0.90 to 0.98.