Low-cost Eye Tracker Research Articles

Using Low Cost Eye-tracking to Verify Decision Aid (Dis)Use

Event Abstract Back to Event Using Low Cost Eye-tracking to Verify Decision Aid (Dis)Use Amanda E. Harwood1*, Carryl L. Baldwin1, Amanda E. Kraft2, Alison M. Perez2, Trevor M. Sands2 and Barlett A. Russell2 1 George Mason University, Human Factors and Applied Cognition, United States 2 Lockheed Martin (United States), United States A current Air Force interest is to design systems that allow one individual to operate several unmanned aerial vehicles (UAVs) at a time. Decision aids that advise the user during operations (e.g. target classification confidence) have the potential to aid performance and decrease workload during these multiple UAV operations, particularly during high risk, high pressure operations. However, in order to be effective UAV operators must calibrate their trust effectively to the capabilities of the decision aid - not becoming complacent (over-trusting) nor under-trusting to the point of disuse. In this study, 42 participants performed a 20-minute multiple UAV simulated operation task using the Supervisory Control Operations User Testbed (SCOUT). The scenario required them to search up to three simulated UAV sensor feeds for a target under either high or low risk conditions. A decision aid suggested whether sensor feed items were targets along with a varying level of confidence in its suggestion. The risk manipulation impacted performance. We used a Gazepoint GP3 eye-tracker to investigate on a trial-by-trial basis how often participants consulted the automated decision aid before making their determination. In the first two and a half minutes participants consulted the decision aid on approximately forty-two percent of trials, declining significantly to approximately ten percent by the last two and a half minutes of the task (see Figure 1). Despite a decrease in consulting, participants performed significantly better as time on task increased from approximately eighty percent accuracy to approximately eighty-eight percent (see Figure 2). Reported mental workload was negatively correlated with decision aid use, meaning that participants who used the decision aid less reported higher mental workload. Participants may have discontinued use of the automated decision aid for several reasons. First, it is possible that the task was manageable without the use of the decision aid. Alternatively, participants may have misunderstood or lacked trust in the decision aid despite a fairly comprehensive training procedure. Regardless of why they discontinued use, verification of use via the eye tracking data provided important information that can be used to guide future work in improving the design of decision aids. Figure Captions: Figure 1. Average percent of participants who checked the decision aid as time on task increased. Figure 2. Average accuracy of participants as time on task increased. Figure 1 Figure 2 Keywords: eye tracking, Automation, Decision aid, Trust, UAV Operations Conference: 2nd International Neuroergonomics Conference, Philadelphia, PA, United States, 27 Jun - 29 Jun, 2018. Presentation Type: Poster Presentation Topic: Neuroergonomics Citation: Harwood AE, Baldwin CL, Kraft AE, Perez AM, Sands TM and Russell BA (2019). Using Low Cost Eye-tracking to Verify Decision Aid (Dis)Use. Conference Abstract: 2nd International Neuroergonomics Conference. doi: 10.3389/conf.fnhum.2018.227.00041 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 02 Apr 2018; Published Online: 27 Sep 2019. * Correspondence: Ms. Amanda E Harwood, George Mason University, Human Factors and Applied Cognition, Fairfax, United States, aharwood@gmu.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Amanda E Harwood Carryl L Baldwin Amanda E Kraft Alison M Perez Trevor M Sands Barlett A Russell Google Amanda E Harwood Carryl L Baldwin Amanda E Kraft Alison M Perez Trevor M Sands Barlett A Russell Google Scholar Amanda E Harwood Carryl L Baldwin Amanda E Kraft Alison M Perez Trevor M Sands Barlett A Russell PubMed Amanda E Harwood Carryl L Baldwin Amanda E Kraft Alison M Perez Trevor M Sands Barlett A Russell Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

An analysis of the suitability of a low-cost eye tracker for assessing the cognitive load of drivers

This paper presents a driving simulator study in which we investigated whether the Eye Tribe eye tracker (ET) is capable of assessing changes in the cognitive load of drivers through oculography and pupillometry. In the study, participants were asked to drive a simulated vehicle and simultaneously perform a set of secondary tasks with different cognitive complexity levels. We measured changes in eye properties, such as the pupil size, blink rate and fixation time. We also performed a measurement with a Detection Response Task (DRT) to validate the results and to prove a steady increase of cognitive load with increasing secondary task difficulty. The results showed that the ET precisely recognizes an increasing pupil diameter with increasing secondary task difficulty. In addition, the ET shows increasing blink rates, decreasing fixation time and narrowing of the attention field with increasing secondary task difficulty. The results were validated with the DRT method and the secondary task performance. We conclude that the Eye Tribe ET is a suitable device for assessing a driver's cognitive load.

Comparing eye trackers by correlating their eye-metric data

Up to now, the potential of eye tracking in science as well as in everyday life has not been fully realized because of the high acquisition cost of trackers. Recently, manufacturers have introduced low-cost devices, preparing the way for wider use of this underutilized technology. As soon as scientists show independently of the manufacturers that low-cost devices are accurate enough for application and research, the real advent of eye trackers will have arrived. To facilitate this development, we propose a simple approach for comparing two eye trackers by adopting a method that psychologists have been practicing in diagnostics for decades: correlating constructs to show reliability and validity. In a laboratory study, we ran the newer, low-cost EyeTribe eye tracker and an established SensoMotoric Instruments eye tracker at the same time, positioning one above the other. This design allowed us to directly correlate the eye-tracking metrics of the two devices over time. The experiment was embedded in a research project on memory where 26 participants viewed pictures or words and had to make cognitive judgments afterwards. The outputs of both trackers, that is, the pupil size and point of regard, were highly correlated, as estimated in a mixed effects model. Furthermore, calibration quality explained a substantial amount of individual differences for gaze, but not pupil size. Since data quality is not compromised, we conclude that low-cost eye trackers, in many cases, may be reliable alternatives to established devices.

Investigating the Use of Two Low Cost Eye Tracking Systems for Detecting Pupillary Response to Changes in Mental Workload

Eye tracking technologies are being utilized at increasing rates within industry and research due to the very recent availability of low cost systems. This paper presents results from a study assessing two eye tracking systems, Gazepoint GP3 and Eye Tribe, both of which are available for under $500 and provide streaming gaze and pupil size data. The emphasis of this research was in evaluating the ability of these eye trackers to identify changes in pupil size which occur as a function of variations in lighting conditions as well as those associated with workload. Ten volunteers participated in an experiment in which a digit span task was employed to manipulate workload as user’s fixated on a monitor which varied in background luminance (black, gray and white). Results revealed that both systems were able to significantly differentiate pupil size differences in high and low workload trials and changes due to the monitor’s luminance. These findings are exceedingly promising for human factors researchers, as they open up the opportunity to augment studies with non-obtrusive, streaming measures of mental workload with technologies available for as little as $100.

Performance of a simple remote video-based eye tracker with GPU acceleration

Eye tracking is a well-established tool that is often utilised in research. There are currently many different types of eye trackers available, but they are either expensive, or provide a relatively low sampling frequency. The eye tracker presented in this paper was developed in an effort to address the lack of low-cost high-speed eye trackers. It utilises the Graphical Processing Unit (GPU) in an attempt to parallelise aspects of the process to localize feature points in eye images to attain higher sampling frequencies. Moreover, the proposed implementation allows for the system to be used on a variety of different GPUs. The developed solution is capable of sampling at frequencies of 200 Hz and higher, while allowing for head movements within an area of 10×6×10 cm and an average accuracy of one degree of visual angle. The entire system can be built for less than 700 euros, and will run on a mid-range laptop.

Sgttoolbox: Utility for controlling SimpleGazeTracker from Psychtoolbox

Eye movement analysis is effective for investigating visual perception and cognition. The cost of conducting eye movement studies has decreased as a result of the recent release of low-cost commercial and open-source eye trackers. However, synchronizing visual stimulus presentation with eye movement recording is still difficult, particularly if the eye tracker does not come with a practical application programming interface. This paper introduces a Matlab/Octave toolbox named Sgttoolbox, which works in conjunction with the widely used experiment control library Psychtoolbox to control a cross-platform open-source eye tracker named SimpleGazeTracker, which is an eye-tracking application of GazeParser software. Hardware and software requirements for Sgttoolbox and its main functions are described. A test of temporal accuracy showed that eye movement sampling frequency was stable when stimulus presentation and recording were performed on a single PC, although better performance was obtained when presentation and recording were performed on separate PCs. Transferring the latest eye position from SimpleGazeTracker to Psychtoolbox script takes 2 to 4 ms on average, which causes a delay in drawing multiple visual stimuli when recording and stimulus presentation were performed on a single PC. When such a transfer delay is not importnat, Sgttoolbox would be a good choice for Psychtoolbox users who wish to conduct eye-tracking studies.

GazeStereo3D

Producing a high quality stereoscopic impression on current displays is a challenging task. The content has to be carefully prepared in order to maintain visual comfort, which typically affects the quality of depth reproduction. In this work, we show that this problem can be significantly alleviated when the eye fixation regions can be roughly estimated. We propose a new method for stereoscopic depth adjustment that utilizes eye tracking or other gaze prediction information. The key idea that distinguishes our approach from the previous work is to apply gradual depth adjustments at the eye fixation stage, so that they remain unnoticeable. To this end, we measure the limits imposed on the speed of disparity changes in various depth adjustment scenarios, and formulate a new model that can guide such seamless stereoscopic content processing. Based on this model, we propose a real-time controller that applies local manipulations to stereoscopic content to find the optimum between depth reproduction and visual comfort. We show that the controller is mostly immune to the limitations of low-cost eye tracking solutions. We also demonstrate benefits of our model in off-line applications, such as stereoscopic movie production, where skillful directors can reliably guide and predict viewers' attention or where attended image regions are identified during eye tracking sessions. We validate both our model and the controller in a series of user experiments. They show significant improvements in depth perception without sacrificing the visual quality when our techniques are applied.

Idiosyncratic Feature-Based Gaze Mapping

It is argued that polynomial expressions that are normally used for remote, video-based, low cost eye tracking systems, are not always ideal to accommodate individual differences in eye cleft, position of the eye in the socket, corneal bulge, astigmatism, etc. A procedure to identify a set of polynomial expressions that will provide the best possible accuracy for a specific individual is proposed. It is also proposed that regression coefficients are recalculated in real-time, based on a subset of calibration points in the region of the current gaze and that a real-time correction is applied, based on the offsets from calibration targets that are close to the estimated point of regard.It was found that if no correction is applied, the choice of polynomial is critically important to get an accuracy that is just acceptable. Previously identified polynomial sets were confirmed to provide good results in the absence of any correction procedure. By applying real-time correction, the accuracy of any given polynomial improves while the choice of polynomial becomes less critical. Identification of the best polynomial set per participant and correction technique in combination with the aforementioned correction techniques, lead to an average error of 0.32° (sd = 0.10°) over 134 participant recordings.The proposed improvements could lead to low-cost systems that are accurate and fast enough to do reading research or other studies where high accuracy is expected at framerates in excess of 200 Hz.

Evaluation of a Low-cost Eye Tracking System for Computer Input

Eye tracking technology has become one of the most popular techniques within the human and computer interaction (HCI) era, this is especially important research for people which have difficulty with speech and movement disabilities. The primary function of this technology is based on a device that tracks the movement of the eye to identify a position or scan a display. Suitable devices for eye movement can then be integrated in concordance with the requirements of the organization. Currently, eye tracking devices are becoming increasingly cheaper which make them an interesting resource for research. Although numerous studies have been conducted involving applications of eye tracking with a low-cost device, few studies have compared the actual eye tracking systems themselves. This paper empirically evaluated the performance of three independent low-cost eye tracking devices, Gazepoint’s GP3, EyeTribe, and DIY (Do-It-Yourselt). The performance evaluation used a multi-directional point-select task based on visual searching and selection to change the ground colour of a circular menu conforming to ISO 9241-9 standards for computer pointing devices. Results indicated that the spatial accuracy and speed were a good reflection of targeted tracking of errors, completion time and throughput. Consequently, the experiment with the target task showed that all devices can be a potentially valuable resource for human computer interaction research. Additionally, this basic result will be used to develop an advanced system for Thai text entry to aid communication for handicapped users.

SET: a pupil detection method using sinusoidal approximation.

Mobile eye-tracking in external environments remains challenging, despite recent advances in eye-tracking software and hardware engineering. Many current methods fail to deal with the vast range of outdoor lighting conditions and the speed at which these can change. This confines experiments to artificial environments where conditions must be tightly controlled. Additionally, the emergence of low-cost eye tracking devices calls for the development of analysis tools that enable non-technical researchers to process the output of their images. We have developed a fast and accurate method (known as “SET”) that is suitable even for natural environments with uncontrolled, dynamic and even extreme lighting conditions. We compared the performance of SET with that of two open-source alternatives by processing two collections of eye images: images of natural outdoor scenes with extreme lighting variations (“Natural”); and images of less challenging indoor scenes (“CASIA-Iris-Thousand”). We show that SET excelled in outdoor conditions and was faster, without significant loss of accuracy, indoors. SET offers a low cost eye-tracking solution, delivering high performance even in challenging outdoor environments. It is offered through an open-source MATLAB toolkit as well as a dynamic-link library (“DLL”), which can be imported into many programming languages including C# and Visual Basic in Windows OS (www.eyegoeyetracker.co.uk).

Eye-tracking capabilities of low-cost EOG system.

This paper presents the design and implementation of a low-cost eye tracking system that allows measuring the rotational angle of the eye and gaze direction in healthy individuals. The system consists of an EOG circuit with simple components that acquire both horizontal and vertical eye movement through regular all-purpose contact electrodes. Then the data are analyzed and translated into corresponding angle values representing the eye rotation angle in both orientations. Results show that horizontal angle measurements are much more accurate than vertical measurements. A discussion regarding the performance and possible improvements is presented.

Low-cost eyetrackers as assistive devices

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GazeParser: an open-source and multiplatform library for low-cost eye tracking and analysis

Eye movement analysis is an effective method for research on visual perception and cognition. However, recordings of eye movements present practical difficulties related to the cost of the recording devices and the programming of device controls for use in experiments. GazeParser is an open-source library for low-cost eye tracking and data analysis; it consists of a video-based eyetracker and libraries for data recording and analysis. The libraries are written in Python and can be used in conjunction with PsychoPy and VisionEgg experimental control libraries. Three eye movement experiments are reported on performance tests of GazeParser. These showed that the means and standard deviations for errors in sampling intervals were less than 1 ms. Spatial accuracy ranged from 0.7° to 1.2°, depending on participant. In gap/overlap tasks and antisaccade tasks, the latency and amplitude of the saccades detected by GazeParser agreed with those detected by a commercial eyetracker. These results showed that the GazeParser demonstrates adequate performance for use in psychological experiments.

Building a Low-Cost Eye-Tracking System

This paper presents the developing of a low-cost eye-tracking system by modifying the commercial-over-the-shelf camera to integrate with the proper-tuned open source drivers and the user-defined application programs. The system configuration is proposed and the gaze-tracking approximated by the least square polynomial mapping is described. Comparisons between other low-cost systems as well as commercial system are provided. Our system obtained the highest image capturing rate of 180 frames per second, and the ISO 9241-Part 9 test performance favored our system, in terms of Response time and Correct response rate. Currently, we are developing gaze-tracking accuracy application. The real time gaze-tracking and the Head Movement Estimation are the issues in future work.

Gliding and saccadic gaze gesture recognition in real time

Eye movements can be consciously controlled by humans to the extent of performing sequences of predefined movement patterns, or 'gaze gestures'. Gaze gestures can be tracked noninvasively employing a video-based eye tracking system. Gaze gestures hold the potential to become an emerging input paradigm in the context of human-computer interaction (HCI) as low-cost eye trackers become more ubiquitous. The viability of gaze gestures as an innovative way to control a computer rests on how easily they can be assimilated by potential users and also on the ability of machine learning algorithms to discriminate in real time intentional gaze gestures from typical gaze activity performed during standard interaction with electronic devices. In this work, through a set of experiments and user studies, we evaluate the performance of two different gaze gestures modalities, gliding gaze gestures and saccadic gaze gestures, and their corresponding real-time recognition algorithms, Hierarchical Temporal Memory networks and the Needleman-Wunsch algorithm for sequence alignment. Our results show that a specific combination of gaze gesture modality, namely saccadic gaze gestures, and recognition algorithm, Needleman-Wunsch, allows for reliable usage of intentional gaze gestures to interact with a computer with accuracy rates higher than 95% and completion speeds of around 1.5 to 2.5 seconds per gesture. The optimal gaze gesture modality and recognition algorithm do not interfere with otherwise standard human-computer gaze interaction, generating very few false positives during real time recognition and positive feedback from the users. These encouraging results and the low cost eye tracking equipment used, open up a new HCI paradigm for the fields of accessibility and interaction with smartphones, tablets, projected displays and traditional desktop computers.

How to Build a Low-Cost Eye-Tracking System

Eye tracking, previously the purview of well-funded laboratories, is now available to any individual who wishes to study gaze patterns. Advances in eye-tracking technology have made it possible for those with meager budgets but an abundance of motivation to engage in studies that examine participants’ eye movements and fixations. This article presents a how-to guide for creating low-cost eye-tracking solutions and includes discussion of optical hardware, tracking software, and data analysis programs. The wider availability of eye-tracking technology ensures that the broader scientific community has access to techniques that can inform design and enhance research.

Development and Validation of a Low-Cost Eye-Tracking Device

Development and Validation of a Low-Cost Eye-Tracking Device

OpenEyes: an open-hardware open-source system for low-cost eye tracking

Eye tracking has long held the promise of being a useful methodology for human computer interaction. However, a number of barriers have stood in the way of the integration of eye tracking into everyday applications, including the intrusiveness, robustness, availability and price of eye-tracking systems. To lower these barriers, we have developed the openEyes system. The system consists of an open-hardware design for a digital eye tracker that can be built from low-cost off-the-shelf components, and a set of open-source software tools for digital image capture, manipulation, and analysis in eye-tracking applications. We expect that the availability of this system will facilitate the development of eye-tracking applications and the eventual integration of eye tracking into the next generation of everyday human computer interfaces. We discuss the methods and technical challenges of low-cost eye tracking as well as the design decisions that produced our current system.

Applications of low-cost eye tracking in telemedicine.

A low-cost, high-resolution system for measuring eye position information and eye movement has been developed. The Vision Control System (VCS) equipment can be worn as a lightweight headset. The ability to operate equipment via eye movement empowers individuals by keeping hands free to perform other tasks. Potential applications of the VCS equipment include its use in surgical training as an on-screen pointing device to highlight areas of interest, use by paramedics to relay information at the scene of an accident, use to examine a radiologist's visual scanning technique in reading films, and use in ophthalmology to monitor eye behaviour.