Discrete-time signal processing
Discrete-time signal processing
Information Visualization: Perception for Design
Information Visualization: Perception for Design
Texturing of Layered Surfaces for Optimal Viewing
IEEE Transactions on Visualization and Computer Graphics
Eye gaze tracking techniques for interactive applications
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Measuring vergence over stereoscopic video with a remote eye tracker
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Visual Thinking: for Design
Experimental researches on gaze-based 3d interaction to stereo image display
Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
Comparison of eye movement metrics recorded at different sampling rates
Proceedings of the Symposium on Eye Tracking Research and Applications
Gaze interaction in the post-WIMP world
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Using eye-tracking to support interaction with layered 3D interfaces on stereoscopic displays
Proceedings of the 19th international conference on Intelligent User Interfaces
Visual attention to wayfinding aids in virtual environments
JVRC '13 Proceedings of the 5th Joint Virtual Reality Conference
| Hi-index | 0.00 |
While determining 2D gaze position using eye tracking is common practice, the efficacy of using eye tracking to measure 3D gaze point in a stereoscopic display has not been carefully studied. In this paper we explore this issue using a custom Wheatstone stereoscope augmented with an eye tracker. In a pilot study, we showed that there is strong evidence that eye vergence measurements do, in fact, track the depth component of the 3D stereo gaze point. In a subsequent full study, we compare depth estimation for a scene viewed in four different ways: without either stereo or motion parallax, without stereo but with motion parallax, with stereo but without motion parallax, and with both stereo and motion parallax. We show a significant effect related to depth from eye vergence for both of the stereo cases, but no effect for the monoscopic cases. Since depth from vergence is very noisy, we use a Butterworth filter to smooth the data and show that this greatly improves the stability of the depth reading without significant lag or loss in accuracy. We also demonstrate that using quadratic regression to perform a depth calibration can greatly improve the accuracy of the depth measurement.