Li, R; Whitmire, E; Stengel, M; Boudaoud, B; Kautz, J; Luebke, D; Patel, S; Li, R; Whitmire, E; Stengel, M; Boudaoud, B; Kautz, J; Luebke, D; Patel, S; Aksit, K; - view fewer (2020) Optical Gaze Tracking with Spatially-Sparse Single-Pixel Detectors. In: Proceedings - 2020 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2020. (pp. pp. 117-126). IEEE: Recife/Porto de Galinhas, Brazil.

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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.

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