Oleg Komogortsev

Texas State University | TxSt

In a prior report (Raju et al., 2023) we concluded that, if the goal was to preserve events such as saccades, microsaccades, and smooth pursuit in eye-tracking recordings, data with sine wave frequencies less than 75 Hz were the signal and data above 75 Hz were noise. Here, we compare five filters in their ability to preserve signal and remove nois...

This manuscript demonstrates an improved model-based approach for synthetic degradation of previously captured eye movement signals. Signals recorded on a high-quality eye tracking sensor are transformed such that their resulting eye tracking signal quality is similar to recordings captured on a low-quality target device. The proposed model improve...

The power requirements of video-oculography systems can be prohibitive for high-speed operation on portable devices. Recently, low-power alternatives such as photosensors have been evaluated, providing gaze estimates at high frequency with a trade-off in accuracy and robustness. Potentially, an approach combining slow/high-fidelity and fast/low-fid...

This paper proposes a novel evaluation framework, termed "critical evaluation periods," for evaluating continuous gaze prediction models. This framework emphasizes prediction performance when it is most critical for gaze prediction to be accurate relative to user perception. Based on perceptual characteristics of the human visual system such as sac...

Prior research states that sine-wave frequencies below 100 Hz carry the eye movement signal, and frequencies above 100 Hz can be considered noise. Here, we explore the biometric implications of this signal/noise distinction. We expect that there are important individual differences in the way subjects move their eyes, and this should lead to reliab...

We present GazeBaseVR, a large-scale, longitudinal, binocular eye-tracking (ET) dataset collected at 250 Hz with an ET-enabled virtual-reality (VR) headset. GazeBaseVR comprises 5,020 binocular recordings from a diverse population of 407 college-aged participants. Participants were recorded up to six times each over a 26-month period, each time per...

In a previous report (Raju et al.,2023) we concluded that, if the goal was to preserve events such as saccades, microsaccades, and smooth pursuit in eye-tracking recordings, data with sine wave frequencies less than 100 Hz (-3db) were the signal and data above 100 Hz were noise. We compare 5 filters in their ability to preserve signal and remove no...

A bstract People coordinate their eye, head, and body movements to gather information from a dynamic environment while maximizing reward and minimizing biomechanical and energetic costs. Such natural behavior is not possible in a laboratory setting where the head and body are usually restrained and the tasks and stimuli used often lack ecological v...

The Fourier theorem proposes that any time-series can be decomposed into a set of sinusoidal frequencies, each with its own phase and amplitude. The literature suggests that some of these frequencies are important to reproduce key qualities of eye-movements (``signal'') and some of these frequencies are not important (``noise''). To understand what...

Many developers of biometric systems start with modest samples before general deployment. However, they are interested in how their systems will work with much larger samples. To assist them, we evaluated the effect of gallery size on biometric performance. Identification rates describe the performance of biometric identification, whereas ROC-based...

We present GazeBaseVR, a large-scale, longitudinal, binocular eye-tracking (ET) dataset collected at 250 Hz with an ET-enabled virtual-reality (VR) headset. GazeBaseVR comprises 5,020 binocular recordings from a diverse population of 407 college-aged participants. Participants were recorded up to six times each over a 26-month period, each time per...

In 1993, Stampe [1993] suggested two "heurisitic" filters that were designed for video-oculography data. Several manufacturers (e.g., SR-Research, Tobii T60 XL and SMI) have employed these filters as an option for recording eye-movements. For the EyeLink family of eye-trackers, these two filters are referred to as standard (STD) or EXTRA. We have i...

Background Nystagmus identification and interpretation is challenging for non-experts who lack specific training in neuro-ophthalmology or neuro-otology. This challenge is magnified when the task is performed via telemedicine. Deep learning models have not been heavily studied in video-based eye movement detection. Methods We developed, trained, a...

Thanks to the eye-tracking sensors that are embedded in emerging consumer devices like the Vive Pro Eye, we demonstrate that it is feasible to deliver user authentication via eye movement biometrics.

Iris-based biometric authentication is a wide-spread biometric modality due to its accuracy, among other benefits. Improving the resistance of iris biometrics to spoofing attacks is an important research topic. Eye tracking and iris recognition devices have similar hardware that consists of a source of infra-red light and an image sensor. This simi...

Manual classification of eye-movements is used in research and as a basis for comparison with automatic algorithms in the development phase. However, human classification will not be useful if it is unreliable and unrepeatable. Therefore, it is important to know what factors might influence and enhance the accuracy and reliability of human classifi...

The permanence of eye movements as a biometric modality remains largely unexplored in the literature. The present study addresses this limitation by evaluating a novel exponentially-dilated convolutional neural network for eye movement authentication using a recently proposed longitudinal dataset known as GazeBase. The network is trained using mult...

Plain convolutional neural networks (CNNs) have been used to achieve state-of-the-art performance in various domains in the past years, including biometric authentication via eye movements. There have been many relatively recent improvements to plain CNNs, including residual networks (ResNets) and densely connected convolutional networks (DenseNets...

Eye movement biometrics (EMB) is a relatively recent behavioral biometric modality that may have the potential to become the primary authentication method in virtual- and augmented-reality (VR/AR) devices due to their emerging use of eye-tracking sensors to enable foveated rendering techniques. However, existing EMB models have yet to demonstrate l...

We present an analysis of the eye tracking signal quality of the HoloLens 2s integrated eye tracker. Signal quality was measured from eye movement data captured during a random saccades task from a new eye movement dataset collected on 30 healthy adults. We characterize the eye tracking signal quality of the device in terms of spatial accuracy, spa...

This paper is a follow-on to our earlier paper (7), which focused on the multimodality of angular offsets. This paper applies the same analysis to the measurement of spatial precision. Following the literature, we refer these measurements as estimates of device precision, but, in fact, subject characteristics clearly affect the measurements. One ty...

This manuscript presents GazeBase, a large-scale longitudinal dataset containing 12,334 monocular eye-movement recordings captured from 322 college-aged participants. Participants completed a battery of seven tasks in two contiguous sessions during each round of recording, including a – (1) fixation task, (2) horizontal saccade task, (3) random obl...

This paper summarizes the OpenEDS 2020 Challenge dataset, the proposed baselines, and results obtained by the top three winners of each competition: (1) Gaze prediction Challenge, with the goal of predicting the gaze vector 1 to 5 frames into the future based on a sequence of previous eye images, and (2) Sparse Temporal Semantic Segmentation Challe...

Typically, the position error of an eye-tracking device is measured as the distance of the eye-position from the target position in two-dimensional space (angular offset). Accuracy is the mean angular offset. The mean is a highly interpretable measure of central tendency if the underlying error distribution is unimodal and normal. However, in the c...

While numerous studies have explored eye movement biometrics since the modality's inception in 2004, the permanence of eye movements remains largely unexplored as most studies utilize datasets collected within a short time frame. This paper presents a convolutional neural network for authenticating users using their eye movements. The network is tr...

The COVID-19 pandemic has devastated individuals, families, and institutions throughout the world. Despite the breakneck speed of vaccine development, the human population remains at risk of further devastation. The decision to not become vaccinated, the protracted rollout of available vaccine, vaccine failure, mutational forms of the SARS virus, w...

This manuscript presents GazeBase, a large-scale longitudinal dataset containing 12,334 monocular eye-movement recordings captured from 322 college-aged subjects. Subjects completed a battery of seven tasks in two contiguous sessions during each round of recording, including a - 1) fixation task, 2) horizontal saccade task, 3) random oblique saccad...

In this work, we tackle the problem of ternary eye movement classification, which aims to separate fixations, saccades and smooth pursuits from the raw eye positional data. The efficient classification of these different types of eye movements helps to better analyze and utilize the eye tracking data. Different from the existing methods that detect...

It is generally accepted that relatively more permanent (i.e., more temporally persistent) traits are more valuable for biometric performance than less permanent traits. Although this finding is intuitive, there is no current work identifying exactly where in the biometric analysis temporal persistence makes a difference. In this paper, we answer t...

The usage of eye tracking sensors is expected to grow in virtual (VR) and augmented reality (AR) platforms. Provided that users of these platforms consent to employing captured eye movement signals for authentication and health assessment, it becomes important to estimate oculomotor plant and brain function characteristics in real time. This paper...

State-of-the-art appearance-based gaze estimation methods, usually based on deep learning techniques, mainly rely on static features. However, temporal trace of eye gaze contains useful information for estimating a given gaze point. For example, approaches leveraging sequential eye gaze information when applied to remote or low-resolution image sce...

We present the second edition of OpenEDS dataset, OpenEDS2020, a novel dataset of eye-image sequences captured at a frame rate of 100 Hz under controlled illumination, using a virtual-reality head-mounted display mounted with two synchronized eye-facing cameras. The dataset, which is anonymized to remove any personally identifiable information on p...

It is generally accepted that relatively more permanent (i.e., more temporally persistent) traits are more valuable for biometric performance than less permanent traits. Although this finding is intuitive, there is no current work identifying exactly where in the biometric analysis temporal persistence makes a difference. In this paper, we answer t...

It is generally accepted that relatively more permanent (i.e., more temporally persistent) traits are more valuable for biometric performance than less permanent traits. Although this finding is intuitive, there is no current work identifying exactly where in the biometric analysis temporal persistence makes a difference. In this paper, we answer t...

In this work, we tackle the problem of ternary eye movement classification, which aims to separate fixations, saccades and smooth pursuits from the raw eye positional data. The efficient classification of these different types of eye movements helps to better analyze and utilize the eye tracking data. Different from the existing methods that detect...

Domain adaptation (DA) has been widely investigated as a framework to alleviate the laborious task of data annotation for image segmentation. Most DA investigations operate under the unsupervised domain adaptation (UDA) setting, where the modeler has access to a large cohort of source domain labeled data and target domain data with no annotations....

We evaluated the data quality of SMI's tethered eye-tracking head-mounted display based on the HTC Vive (ET-HMD) during a random saccade task. We measured spatial accuracy, spatial precision, temporal precision, linearity, and crosstalk. We proposed the use of a non-parametric spatial precision measure based on the median absolute deviation (MAD)....

Photosensor oculography (PS-OG) eye movement sensors offer desirable performance characteristics for integration within wireless head mounted devices (HMDs), including low power consumption and high sampling rates. To address the known performance degradation of these sensors due to HMD shifts, various machine learning techniques have been proposed...

Photosensor oculography (PSOG) is a promising solution for reducing the computational requirements of eye tracking sensors in wireless virtual and augmented reality platforms. This paper proposes a novel machine learning-based solution for addressing the known performance degradation of PSOG devices in the presence of sensor shifts. Namely, we intr...

If you have a target level of biometric performance (e.g. EER = 5% or 0.1%), how many units of unique information (uncorrelated features) are needed to achieve that target? We show, for normally distributed features, that the answer to that question depends on the temporal persistence of the feature set. We address these questions with synthetic fe...

The relationship between the number of subjects included in a biometric authentication study and biometric performance assesed with equal error rate (EER) is not well studied. In the present paper, we use both synthetic and real data to study this relationship. Although we and others had hypothesized that more information would be required to authe...

The proper classification of major eye movements, saccades, fixations, and smooth pursuits, remains essential to utilizing eye-tracking data. There is difficulty in separating out smooth pursuits from the other behavior types, particularly from fixations. To this end, we propose a new offline algorithm, I-VDT-HMM, for tertiary classification of eye...

We built a custom video-based eye-tracker that saves every video frame as a full resolution image (MJPEG). Images can be processed offline for the detection of ocular features, including the pupil and corneal reflection (First Purkinje Image, P1) position. A comparison of multiple algorithms for detection of pupil and corneal reflection can be perf...

The importance of normalizing biometric features or matching scores is understood in the multimodal biometric case, but there is less attention to the unimodal case. Prior reports assess the effectiveness of normalization directly on biometric performance. We propose that this process is logically comprised of two independent steps: (1) methods to...

Principal components analysis (PCA) is a common method employed for dimension reduction in the biometric context. PCA components can be left raw, in which case the first component has the greatest variance and the last component has the least variance, or the components can be normalized to equal variance. In this paper we study the effect of this...

Principal components analysis (PCA) is a common method employed for dimension reduction in the biometric context. PCA components can be left raw, in which case the first component has the greatest variance and the last component has the least variance, or the components can be normalized to equal variance. In this paper we study the effect of this...

Saccade landing position prediction algorithms are a promising approach for improving the performance of gaze-contingent rendering systems. Amongst the various techniques considered in the literature, velocity profile methods operate by first fitting a window of velocity data obtained at the initiation of the saccadic event to a model profile known...

Tracking users' gaze in virtual reality headsets allows natural and intuitive interaction with virtual avatars and virtual objects. Moreover, a technique known as foveated rendering can help save computational resources and enable hi-resolution but lightweight virtual reality technologies. Predominantly, eye-tracking hardware in modern VR headsets...

As eye tracking can reduce the computational burden of virtual reality devices through a technique known as foveated rendering, we believe not only that eye tracking will be implemented in all virtual reality devices, but that eye tracking biometrics will become the standard method of authentication in virtual reality. Thus, we have created a real-...

Virtual reality (VR) is employed in a variety of different applications. It is our belief that eye-tracking is going to be a part of the majority of VR devices that will reduce computational burden via a technique called foveated rendering and will increase the immersion of the VR environment. A promising technique to achieve low energy, fast, and...

A common aspect of individuality is our subjective preferences in evaluation of reward and effort. The neural circuits that evaluate these commodities influence circuits that control our movements, raising the possibility that vigor differences between individuals may also be a trait of individuality, reflecting a willingness to expend effort. In c...

Nystrӧm and Holmqvist have published a method for the classification of eye movements during reading (ONH) (Nyström & Holmqvist, 2010). When we applied this algorithm to our data, the results were not satisfactory, so we modified the algorithm (now the MNH) to better classify our data. The changes included: (1) reducing the amount of signal filteri...

This work presents a study of an extensive set of 101 categories of eye movement features from three types of eye movement events: fixations, saccades, and post-saccadic oscillations. We present a unified framework of methods for the extraction of features that describe the temporal, positional and dynamic characteristics of eye movements. We perfo...

This paper introduces and evaluates a novel hybrid technique that fuses two eye-tracking methodologies: photosensor oculography and video oculography. The main concept of the technique is to use a few fast and power-economic photosensors as the core mechanism for performing high speed eye-tracking, while in parallel, operate a video sensor at low s...

We present software to detect noise in eye position signals from video-based eye-tracking systems that depend on accurate pupil and corneal reflection position estimation. When such systems transiently fail to properly detect the pupil or the corneal reflection due to occlusion from eyelids, eye lashes or various shadows, the estimated gaze positio...

We create synthetic biometric databases to study general, fundamental, biometric principles. First, we check the validity of the synthetic database design by comparing it to real data in terms of biometric performance. The real data used for this validity check was from an eye-movement related biometric database. Next, we employ our database to eva...

This paper presents a renewed overview of photosensor oculography (PSOG), an eye-tracking technique based on the principle of using simple photosensors to measure the amount of reflected (usually infrared) light when the eye rotates. Photosensor oculography can provide measurements with high precision, low latency and reduced power consumption, and...

The calculation of the intraclass correlation coefficient. (DOCX)