Calibration-Free Gaze Estimation Using Human Gaze Patterns

• Published in: 2013 IEEE International Conference on Computer Vision pp. 137 - 144
• Main Authors: Alnajar, Fares, Gevers, Theo, Valenti, Roberto, Ghebreab, Sennay
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.12.2013
• Subjects: Accuracy; Calibration; Cameras; Chin; Computer vision; Estimates; Estimation; Estimators; Human; Manifolds; Pattern matching; Rest; Visualization; Webcams
• ISSN: 1550-5499; 2380-7504
• DOI: 10.1109/ICCV.2013.24

We present a novel method to auto-calibrate gaze estimators based on gaze patterns obtained from other viewers. Our method is based on the observation that the gaze patterns of humans are indicative of where a new viewer will look at. When a new viewer is looking at a stimulus, we first estimate a topology of gaze points (initial gaze points). Next, these points are transformed so that they match the gaze patterns of other humans to find the correct gaze points. In a flexible uncalibrated setup with a web camera and no chin rest, the proposed method was tested on ten subjects and ten images. The method estimates the gaze points after looking at a stimulus for a few seconds with an average accuracy of 4:3°. Although the reported performance is lower than what could be achieved with dedicated hardware or calibrated setup, the proposed method still provides a sufficient accuracy to trace the viewer attention. This is promising considering the fact that auto-calibration is done in a flexible setup, without the use of a chin rest, and based only on a few seconds of gaze initialization data. To the best of our knowledge, this is the first work to use human gaze patterns in order to auto-calibrate gaze estimators.