We present a method for optimization-based recovery of eye motion from rolling shutter video of the retina. Our approach formulates eye tracking as an optimization problem that jointly estimates the retina’s motion and appearance using convex optimization and a constrained version of gradient descent. By incorporating the rolling shutter imaging model into the formulation of our joint optimization, we achieve state-of-the-art accuracy both offline and in real-time. We apply our method to retina video captured with an adaptive optics scanning laser ophthalmoscope (AOSLO), demonstrating eye tracking at 1 kHz with accuracies below one arcminute—over an order of magnitude higher than conventional eye tracking systems.

Current eye-tracking techniques rely primarily on video-based tracking of components of the anterior surfaces of the eye. However, these trackers have several limitations. Their limited resolution precludes study of small fixational eye motion. Furthermore, many of these trackers rely on calibration procedures that do not offer a way to validate their eye motion traces. By comparison, retinal-image-based trackers can track the motion of the retinal image directly, at frequencies greater than 1kHz and with subarcminute accuracy. The retinal image provides a way to validate the eye position at any point in time, offering an unambiguous record of eye motion as a reference for the eye trace. The benefits of using scanning retinal imaging systems as eye trackers, however, comes at the price of different problems that are not present in video-based systems, and need to be solved to obtain robust eye traces. The current abstract provides an overview of retinal-image-based eye tracking methods, provides preliminary eye-tracking results from a tracking scanning-laser ophthalmoscope (TSLO), and proposes a new binocular line-scanning eye-tracking system.

Recent advances in high magnification retinal imaging have allowed for visualization of individual retinal photoreceptors, but these systems also suffer from distortions due to fixational eye motion. Algorithms developed to remove these distortions have the added benefit of providing arc second level resolution of the eye movements that produce them. The system also allows for visualization of targets on the retina, allowing for absolute retinal position measures to the level of individual cones. This paper will describe the process used to remove the eye movement artifacts and present analysis of their spectral characteristics. We find a roughly 1/f amplitude spectrum similar to that reported by Findlay (1971) with no evidence for a distinct tremor component.