FlatTrack: Eye-tracking with ultra-thin lensless cameras
Purvam Jain, Althaf M. Nazar, Salman S. Khan, Kaushik Mitra, Praneeth, Chakravarthula

TL;DR
This paper introduces FlatTrack, a compact, lensless eye gaze tracking system that is ultra-flat, lightweight, and capable of real-time performance, suitable for integration into AR/VR headsets.
Contribution
The work presents a novel lensless, mask-based camera design combined with a deep neural network for ultra-flat, high-performance eye gaze tracking in wearable devices.
Findings
Performs on par with traditional lens-based trackers
Achieves real-time gaze tracking at over 125 fps
Significantly reduces the form factor of eye trackers
Abstract
Existing eye trackers use cameras based on thick compound optical elements, necessitating the cameras to be placed at focusing distance from the eyes. This results in the overall bulk of wearable eye trackers, especially for augmented and virtual reality (AR/VR) headsets. We overcome this limitation by building a compact flat eye gaze tracker using mask-based lensless cameras. These cameras, in combination with co-designed lightweight deep neural network algorithm, can be placed in extreme close proximity to the eye, within the eyeglasses frame, resulting in ultra-flat and lightweight eye gaze tracker system. We collect a large dataset of near-eye lensless camera measurements along with their calibrated gaze directions for training the gaze tracking network. Through real and simulation experiments, we show that the proposed gaze tracking system performs on par with conventional…
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Taxonomy
TopicsVirtual Reality Applications and Impacts · Visual Attention and Saliency Detection · Gaze Tracking and Assistive Technology
