Paper Info
Title
Optical Gaze Tracking with Spatially-Sparse Single-Pixel Detectors
Abstract
Gaze tracking is an essential component of next generation displays for virtual reality and augmented reality applications. Traditional camera-based gaze trackers used in next generation displays are known to be lacking in one or multiple of the following metrics: power consumption, cost, computational complexity, estimation accuracy, latency, and form-factor. We propose the use of discrete photodiodes and light-emitting diodes (LEDs) as an alternative to traditional camera-based gaze tracking approaches while taking all of these metrics into consideration. We begin by developing a rendering-based simulation framework for understanding the relationship between light sources and a virtual model eyeball. Findings from this framework are used for the placement of LEDs and photodiodes. Our first prototype uses a neural network to obtain an average error rate of 2.67° at 400 Hz while demanding only 16 mW. By simplifying the implementation to using only LEDs, duplexed as light transceivers, and more minimal machine learning model, namely a light-weight supervised Gaussian process regression algorithm, we show that our second prototype is capable of an average error rate of 1.57° at 250 Hz using 800 mW.
Year
DOI
Venue
2020
10.1109/ISMAR50242.2020.00033
2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
Keywords
DocType
ISSN
Human-centered computing,Ubiquitous and mobile computing,Ubiquitous and mobile devices,Computer systems organization,Embedded and cyber-physical systems,Sensors and actuators
Conference
1554-7868
ISBN
Citations 
PageRank 
978-1-7281-8509-5
0
0.34
References 
Authors
34
8
Name
Order
Citations
PageRank
Richard Y. M. Li1369.97
Eric Whitmire201.35
Michael Stengel31209.80
Ben Boudaoud4163.48
Jan Kautz500.34
David Luebke62196140.84
Shwetak N. Patel72967211.74
Kaan Aksit8606.34