Real-time and Offline Filters for Eye Tracking

An eye tracker makes it possible to record the gaze point of a person looking at for example a computer monitor. Modern techniques are very flexible and allow the user to behave naturally without the need of cumbersome equipment such as special contact lenses or electrical probes. This is valuable in psychological research, marketing research and Human Computer Interaction. Eye trackers also give people who are severely paralyzed and unable to type and speak means to communicate using their eyes. Measurement noise makes the use of digital filters necessary. An example is an eye-controlled cursor for a desktop environment such as Windows. The cursor has to be stable enough to allow the user to select folders, icons or other items of interest. While this type of application requires a fast real-time filter, others are less sensitive to processing time but demand an even higher level of accuracy. This work explores three areas of eye tracking filtration and aims at enhancing the performance of the filters used in the eye tracking systems built by Tobii Technology, Sweden. First, a post-processing algorithm to find fixations in raw gaze data is detailed. Second, modifications to an existing reading detection algorithm are described to make it more robust to natural irregularities in reading patterns. Third, a real-time filter for an eye-controlled cursor to be used in a desktop environment is designed using a low-pass filter in parallel with a change detector. The fixation filter produced fewer false fixations and was also able to detect fixations lying spatially closer together than the previously used filter. The reading detection algorithm was shown to be robust to natural irregularities in reading such as revisits to previously read text or skipped paragraphs. The eye-cursor filter proved to respond quicker than the previously used moving average filter while maintaining a high level of noise attenuation