Perceptual User Interfaces Logo
University of Stuttgart Logo

Combining Gaze Estimation and Optical Flow for Pursuits Interaction

Mihai Bâce, Vincent Becker, Chenyang Wang, Andreas Bulling

Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA), pp. 1-10, 2020.

Best paper award



We propose a novel method to detect pursuits using a single off-the-shelf RGB camera. Our method jointly analyses the eye gaze direction and optical flow in the eye region to identify the target the user is following.

Abstract

Pursuit eye movements have become widely popular because they enable spontaneous eye-based interaction. However, existing methods to detect smooth pursuits require special-purpose eye trackers. We propose the first method to detect pursuits using a single off-the-shelf RGB camera in unconstrained remote settings. The key novelty of our method is that it combines appearance-based gaze estimation with optical flow in the eye region to jointly analyse eye movement dynamics in a single pipeline. We evaluate the performance and robustness of our method for different numbers of targets and trajectories in a 13-participant user study. We show that our method not only outperforms the current state of the art but also achieves competitive performance to a consumer eye tracker for a small number of targets. As such, our work points towards a new family of methods for pursuit interaction directly applicable to an ever-increasing number of devices readily equipped with cameras.

Links


BibTeX

@inproceedings{bace20_etra, title = {Combining Gaze Estimation and Optical Flow for Pursuits Interaction}, author = {Bâce, Mihai and Becker, Vincent and Wang, Chenyang and Bulling, Andreas}, year = {2020}, booktitle = {Proc. ACM International Symposium on Eye Tracking Research and Applications (ETRA)}, doi = {10.1145/3379155.3391315}, pages = {1-10} }