Abstract
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Eye tracking has become an essential human-machine interaction modality in virtual and augmented reality (VR/AR) applications requiring high throughput (e.g., >240 FPS), small form-factor, and enhanced visual privacy. Existing eye tracking systems have adopted bulky lens-based cameras, and thus suffer from both a large form-factor and high communication cost between the camera and backend processor. This work presents a camera, algorithm, and accelerator co-designed lensless eye tracking system dubbed EyeCoD, which to the best of our knowledge is the first to provide a general front-end eye tracking solution for AR/VR while satisfying the requirements for both high throughput and smaller form-factor. Specifically, EyeCoD integrates system-, algorithm-, and accelerator-level techniques to boost system efficiency without sacrificing the eye tracking accuracy. We believe that our EyeCoD system will pave the way for next-generation eye tracking solutions in VR/AR and can shed light on future innovations for intelligent imaging systems.</i>
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