The human eye offers a fascinating window into an individual’s health, cognitive attention, and decision making, but we lack the ability to continually measure these parameters in the natural environment. The challenges lie in: a) handling the complexity of continuous high-rate sensing from a camera and processing the image stream to estimate eye parameters, and b) dealing with the wide variability in illumination conditions in the natural environment. This paper explores the power–robustness tradeoffs inherent in the design of a wearable eye tracker, and proposes a novel staged architecture that enables graceful adaptation across the spectrum of real-world illumination. We propose CIDER, a system that operates in a highly optimized low-power mode under indoor settings by using a fast Search-Refine controller to track the eye, but detects when the environment switches to more challenging outdoor sunlight and switches models to operate robustly under this condition. Our design is holistic and tackles a) power consumption in digitizing pixels, estimating pupillary parameters, and illuminating the eye via near-infrared, b) error in estimating pupil center and pupil dilation, and c) model training procedures that involve zero effort from a user. We demonstrate that CIDER can estimate pupil center with error less than two pixels (0.6°), and pupil diameter with error of one pixel (0.22mm). Our end-to-end results show that we can operate at power levels of roughly 7mW at a 4Hz eye tracking rate, or roughly 32mW at rates upwards of 250Hz.
Excerpted from "CIDER: Enabling Robustness-Power Tradeoffs on a Computational Eyeglass," from Proceedings of the 21st Annual ACM International Conference on Mobile Computing and Networking with permission. http://dl.acm.org/citation.cfm?id=2790096 © ACM 2015. The eye is a truly unique and fascinating piece of physiology. Through it, organisms take in massive amounts of sensory data; through it, they also communicate emotion and intent both consciously and unconsciously. It is so tightly coupled with the operation of the brain that even slight mental blocks like being tired are measurable through eye movements. Eye-related research has long worn out the cliche "the eyes are the window to the soul," and this is largely because there is a deeper truth behind this phrase that has come to light in the last several decades of psychology and neurology research. In short, we now understand that the eyes are the best window to the mind. (Kahneman 2011).
The human eye offers a fascinating window into an individual’s health, cognitive attention, and decision making, but we lack the ability to continually measure these parameters in the natural environment. We demonstrate CIDER, a system that operates in a highly optimized low-power mode under indoor settings by using a fast Search-Refine controller to track the eye, but detects when the environment switches to more challenging outdoor sunlight and switches models to operate robustly under this condition. Our design is holistic and tackles a) power consumption in digitizing pixels, estimating pupillary parameters, and illuminating the eye via near-infrared and b) error in estimating pupil center and pupil dilation. We demonstrate that CIDER can estimate pupil center with error less than two pixels (0.6°), and pupil diameter with error of one pixel (0.22mm). Our end-to-end results show that we can operate at power levels of roughly 7mW at a 4Hz eye tracking rate, or roughly 32mW at rates upwards of 250Hz.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.