Human Eye Movements Research Articles

Online Learners' Reading Ability Detection Based on Eye-Tracking Sensors.

The detection of university online learners’ reading ability is generally problematic and time-consuming. Thus the eye-tracking sensors have been employed in this study, to record temporal and spatial human eye movements. Learners’ pupils, blinks, fixation, saccade, and regression are recognized as primary indicators for detecting reading abilities. A computational model is established according to the empirical eye-tracking data, and applying the multi-feature regularization machine learning mechanism based on a Low-rank Constraint. The model presents good generalization ability with an error of only 4.9% when randomly running 100 times. It has obvious advantages in saving time and improving precision, with only 20 min of testing required for prediction of an individual learner’s reading ability.

Point with your eyes not with your hands

The emergence of gesture based controls like the Microsoft Kinect provides new opportunities for creative and innovative methods of human computer interaction. However, such devices are not without their limitations. The gross-motor movements of gestural interaction present physical limitations that may negatively affect interaction speed, accuracy, and workload, and subsequently affect the design of system interfaces and inputs. Conversely, interaction methods such as eye tracking require little physical effort, leveraging the unconscious and natural behaviors of human eye-movements as inputs. Unfortunately, eye tracking, in most cases, is limited to a simple pointing device. However, this research shows by combining these interactions into gaze-based gestural controls it is possible to overcome the limitations of each method, improving interaction performance by associating gestural commands to interface elements within a user’s field of view.

Human short-latency ocular vergence responses produced by interocular velocity differences.

We studied human short-latency vergence eye movements to a novel stimulus that produces interocular velocity differences without a changing disparity signal. Sinusoidal luminance gratings moved in opposite directions (left vs. right; up vs. down) in the two eyes. The grating seen by each eye underwent ¼-wavelength shifts with each image update. This arrangement eliminated changing disparity cues, since the phase difference between the eyes alternated between 0° and 180°. We nevertheless observed robust short-latency vergence responses (VRs), whose sign was consistent with the interocular velocity differences (IOVDs), indicating that the IOVD cue in isolation can evoke short-latency VRs. The IOVD cue was effective only when the images seen by the two eyes overlapped in space. We observed equally robust VRs for opposite horizontal motions (left in one eye, right in the other) and opposite vertical motions (up in one eye, down in the other). Whereas the former are naturally generated by objects moving in depth, the latter are not part of our normal experience. To our knowledge, this is the first demonstration of a behavioral consequence of vertical IOVD. This may reflect the fact that some neurons in area MT are sensitive to these motion signals (Czuba, Huk, Cormack, & Kohn, 2014). VRs were the strongest for spatial frequencies in the range of 0.35–1 c/°, much higher than the optimal spatial frequencies for evoking ocular-following responses observed during frontoparallel motion. This suggests that the two motion signals are detected by different neuronal populations. We also produced IOVD using moving uncorrelated one-dimensional white-noise stimuli. In this case the most effective stimuli have low speed, as predicted if the drive originates in neurons tuned to high spatial frequencies (Sheliga, Quaia, FitzGibbon, & Cumming, 2016).

A study of artificial eyes for the measurement of precision in eye-trackers.

The precision of an eye-tracker is critical to the correct identification of eye movements and their properties. To measure a system's precision, artificial eyes (AEs) are often used, to exclude eye movements influencing the measurements. A possible issue, however, is that it is virtually impossible to construct AEs with sufficient complexity to fully represent the human eye. To examine the consequences of this limitation, we tested currently used AEs from three manufacturers of eye-trackers and compared them to a more complex model, using 12 commercial eye-trackers. Because precision can be measured in various ways, we compared different metrics in the spatial domain and analyzed the power-spectral densities in the frequency domain. To assess how precision measurements compare in artificial and human eyes, we also measured precision using human recordings on the same eye-trackers. Our results show that the modified eye model presented can cope with all eye-trackers tested and acts as a promising candidate for further development of a set of AEs with varying pupil size and pupil-iris contrast. The spectral analysis of both the AE and human data revealed that human eye data have different frequencies that likely reflect the physiological characteristics of human eye movements. We also report the effects of sample selection methods for precision calculations. This study is part of the EMRA/COGAIN Eye Data Quality Standardization Project.

The analysis of the influence of fractal structure of stimuli on fractal dynamics in fixational eye movements and EEG signal.

One of the major challenges in vision research is to analyze the effect of visual stimuli on human vision. However, no relationship has been yet discovered between the structure of the visual stimulus, and the structure of fixational eye movements. This study reveals the plasticity of human fixational eye movements in relation to the ‘complex’ visual stimulus. We demonstrated that the fractal temporal structure of visual dynamics shifts towards the fractal dynamics of the visual stimulus (image). The results showed that images with higher complexity (higher fractality) cause fixational eye movements with lower fractality. Considering the brain, as the main part of nervous system that is engaged in eye movements, we analyzed the governed Electroencephalogram (EEG) signal during fixation. We have found out that there is a coupling between fractality of image, EEG and fixational eye movements. The capability observed in this research can be further investigated and applied for treatment of different vision disorders.

Eye movements between saccades: Measuring ocular drift and tremor

Intersaccadic periods of fixation are characterized by incessant retinal motion due to small eye movements. While these movements are often disregarded as noise, the temporal modulations they introduce to retinal receptors are significant. However, analysis of these input modulations is challenging because the intersaccadic eye motion is close to the resolution limits of most eyetrackers, including widespread pupil-based video systems. Here, we analyzed in depth the limits of two high-precision eyetrackers, the Dual-Purkinje Image and the scleral search coil, and compared the intersaccadic eye movements of humans to those of a non-human primate. By means of a model eye we determined that the resolution of both techniques is sufficient to reliably measure intersaccadic ocular activity up to approximately 80Hz. Our results show that the characteristics of ocular drift are remarkably similar in the two species; a clear deviation from a scale-invariant spectrum occurs in the range between 50 and 100Hz, generally attributed to ocular tremor, leading to intersaccadic retinal speeds as high as 1.5deg/s. The amplitude of this deviation differs on the two axes of motion. In addition to our experimental observations, we suggest basic guidelines to evaluate the performance of eyetrackers and to optimize experimental conditions for the measurement of ocular drift and tremor.

Biometric Recognition via Eye Movements

Previous research shows that human eye movements can serve as a valuable source of information about the structural elements of the oculomotor system and they also can open a window to the neural functions and cognitive mechanisms related to visual attention and perception. The research field of eye movement-driven biometrics explores the extraction of individual-specific characteristics from eye movements and their employment for recognition purposes. In this work, we present a study for the incorporation of dynamic saccadic features into a model of eye movement-driven biometrics. We show that when these features are added to our previous biometric framework and tested on a large database of 322 subjects, the biometric accuracy presents a relative improvement in the range of 31.6--33.5% for the verification scenario, and in range of 22.3--53.1% for the identification scenario. More importantly, this improvement is demonstrated for different types of visual stimulus (random dot, text, video), indicating the enhanced robustness offered by the incorporation of saccadic vigor and acceleration cues.

Cerebral Functional Response during Eyelid Opening/Closing with Bell's Phenomenon and Volitional Vertical Eye Movements in Humans.

Bell's phenomenon is a physiological phenomenon wherein the eye ball involuntarily rolls upward during eyelid closing. Although this phenomenon occurs in healthy individuals, the neural mechanism related to Bell's phenomenon has not yet been identified. We aimed to investigate the brain regions relevant to Bell's phenomenon and volitional eye movement using [15O] H2O and positron emission tomography (PET). We measured regional cerebral blood flow (rCBF) in 8 normal subjects under 3 conditions: at rest with eyes closed, during opening and closing of the eyelids in response to sound stimuli (lid opening/closing), and during vertical movement of the eyes with lids closed in response to sound stimuli (volitional eye movement). The supplementary motor area (SMA) proper, right superior temporal gyrus, right insular cortex and left angular gyrus were activated during lid opening/closing. The right frontal eye field (FEF), pre-SMA, left primary motor area, right angular gyrus, and SMA proper were activated during volitional eye movement. The SMA proper was active during both tasks, while the FEF and pre-SMA were active during volitional eye movement, but not during eyelid opening/closing. A comparison of activation during volitional eye movements and lid opening/closing tasks revealed a relative increase in rCBF in the FEF. There were no areas that are activated in relation to Bell's phenomenon. In conclusion, activation in the FEF mainly occurs during volitional eye movement. Since Bell's phenomenon is a reflexive eye movement, the FEF is scarcely concerned in Bell's phenomenon.

Fetal Ultrasound Image Classification Using a Bag-of-words Model Trained on Sonographers’ Eye Movements

The acquisition of fetal biometric measurements via 2-D B-Mode ultrasound (US) scans is crucial for fetal monitoring. However, acquiring standardised head, abdominal and femoral image planes is challenging due to variable image quality. There remains a significant discrepancy between the way automated computer vision algorithms and human sonographers perform this task; this paper contributes to the attempt to bridge this gap by building knowledge of US image perception into a pipeline for classifying images obtained during 2-D fetal US scans. We record the eye movements of 10 participants performing 4 2-D US scans each, on a phantom fetal model at varying orientations. We analyse their eye movements to establish which high-level constraints and visual cues are used to localise the standardised abdominal plane. We then build a vocabulary of visual words trained on SURF descriptors extracted around eye fixations, and use the resulting bag of words model to classify head, abdominal and femoral image frames acquired during 10 clinical US scans and 10 further phantom US scans. On phantom data, we achieve classification accuracies of 89%, 87% and 85% for the head, abdominal and femoral images respectively. On clinical data, we achieve classification accuracies of 76%, 68% and 64% for the head, abdominal and femoral images respectively. This constitutes the first insight into image perception during real time US scanning, and a proof of concept for training bag of words models for US image analysis on human eye movements.

滑動性追跡眼球運動におけるヒトのタイミング適応の特性

視覚情報の入力のタイミングは運動制御の調節や適応に重要な役割を果たしている. 先行研究から, 急激な速度変化を伴う視標の動きを繰り返し眼で追うことによって, 滑動性追跡眼球運動 (パーシュート) に適応的変化が起こることが知られている. 本研究では, 視標の速度変化のタイミングに注目し, 変化時間に同期したパーシュート適応が起こるかについて検討した. その結果, ヒトのパーシュートにタイミング特異的な適応 (タイミング適応) が認められた. さらに, 先行研究よりヒトとサルの眼球運動の類似性が報告されているが, タイミング適応の場合, ヒトとサルでは適応パターンが異なることも明らかになった. これらの結果から, パーシュートのタイミング適応はヒト特有の時間予測を含めたタイミング制御機構に起因していることが示唆された.

Simulate Human Saccadic Scan-Paths in Target Searching

Human saccade is a dynamic process of information pursuit. There are many methods using either global context or local context cues to model human saccadic scan-paths. In contrast to them, this paper introduces a model for gaze movement control using both global and local cues. To test the performance of this model, an experiment is done to collect human eye movement data by using an SMI iVIEW X Hi-Speed eye tracker with a sampling rate of 1250 Hz. The experiment used a two-by-four mixed design with the location of the targets and the four initial positions. We compare the saccadic scan-paths generated by the proposed model against human eye movement data on a face benchmark dataset. Experimental results demonstrate that the simulated scan-paths by the proposed model are similar to human saccades in term of the fixation order, Hausdorff distance, and prediction accuracy for both static fixation locations and dynamic scan-paths.

Visual Focus of Attention Actively Associates Relevancy in Eye Movements

<p><em>Advancements in the studies of eye movements have excelled beyond frontiers and transited into the phase of next generation splendidly. The business applications, like online shopping, advertisement, web designing, search engine optimization, of eye movement studies in real world scenarios have started to dominate as well. Tracking of eye movements can communicate the underlying mechanism of visual perception and dynamics of humans’ cognition that are of prime concerns for a number of social, economic, and scientific purposes. In this study, we conducted a series of eye tracking experiments to verify our hypothesis that during human eye movements, the visual focus of attention dynamically associated relevant constituents of artistic portrait. We collected the eye movement data of participants who regarded artistic portraits during active viewing. The trails produced from eye tracking system during portrait viewing traced connected focuses of attention in eye movements based on relevancy in visual contexts. These experimental facts validated the hypothesis that visual focus of attention actively associated relevancy in eye movements.</em></p>

Loss of Afferent Vestibular Input Produces Central Adaptation and Increased Gain of Vestibular Prosthetic Stimulation.

Implanted vestibular neurostimulators are effective in driving slow phase eye movements in monkeys and humans. Furthermore, increases in slow phase velocity and electrically evoked compound action potential (vECAP) amplitudes occur with increasing current amplitude of electrical stimulation. In intact monkeys, protracted intermittent stimulation continues to produce robust behavioral responses and preserved vECAPs. In lesioned monkeys, shorter duration studies show preserved but with somewhat lower or higher velocity behavioral responses. It has been proposed that such changes are due to central adaptive changes in the electrically elicited vestibulo-ocular reflex (VOR). It is equally possible that these differences are due to changes in the vestibular periphery in response to activation of the vestibular efferent system. In order to investigate the site of adaptive change in response to electrical stimulation, we performed transtympanic gentamicin perfusions to induce rapid changes in vestibular input in monkeys with long-standing stably functioning vestibular neurostimulators, disambiguating the effects of implantation from the effects of ototoxic lesion. Gentamicin injection was effective in producing a large reduction in natural VOR only when it was performed in the non-implanted ear, suggesting that the implanted ear contributed little to the natural rotational response before injection. Injection of the implanted ear produced a reduction in the vECAP responses in that ear, suggesting that the intact hair cells in the non-functional ipsilateral ear were successfully lesioned by gentamicin, reducing the efficacy of stimulation in that ear. Despite this, injection of both ears produced central plastic changes that resulted in a dramatically increased slow phase velocity nystagmus elicited by electrical stimulation. These results suggest that loss of vestibular afferent activity, and a concurrent loss of electrically elicited vestibular input, produces an increase in the efficacy of a vestibular neurostimulator by eliciting centrally adapted behavioral responses without concurrent adaptive increase of galvanic afferent activation in the periphery.

Researching Students Gifted in Science Using the Method of Eye Tracking

Eye Tracking is a modern diagnostic method which has been recently applied in several studies. This method is based on observing human eye movement, monitoring a spot an eye is focused on, its distance, or the time duration of such focus. The course of the look, the sequence of eye fixations and movement can be widely used in cognitive sciences. This is where we class the area of pedagogical-psychological research of gifted students.

The influence of color during continuity cuts in edited movies: an eye-tracking study

Professionally edited videos entail frequent editorial cuts --- that is, abrupt image changes from one frame to another. The impact of these cuts on human eye movements is currently not well understood. In the present eye-tracking study, we experimentally gauged the degree to which color and visual continuity contributed to viewers' eye movements following cinematic cuts. In our experiment, viewers were presented with two edited action sports movies on the same screen but they were instructed to watch and keep their gaze on only one of these movies. Crucially, the movies were frequently interrupted and continued after a short break either at the same or at switched locations. Hence, viewers needed to rapidly recognize the continuation of the relevant movie and re-orient their gaze toward it. Properties of saccadic eye movements following each interruption probed the recognition of the relevant movie after a cut. Two key findings were that (i) memory co-determines attention after cuts in edited videos, resulting in faster re-orientation toward scene continuations when visual continuity across the interruption is high than when it is low, and (ii) color contributes to the guidance of attention after cuts, but its benefit largely rests upon enhanced discrimination of relevant from irrelevant visual information rather than memory. Results are discussed with regard to previous research on eye movements in movies and recognition processes. Possible future directions of research are outlined.

Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for Visual Recognition.

Systems based on bag-of-words models from image features collected at maxima of sparse interest point operators have been used successfully for both computer visual object and action recognition tasks. While the sparse, interest-point based approach to recognition is not inconsistent with visual processing in biological systems that operate in `saccade and fixate' regimes, the methodology and emphasis in the human and the computer vision communities remains sharply distinct. Here, we make three contributions aiming to bridge this gap. First, we complement existing state-of-the art large scale dynamic computer vision annotated datasets like Hollywood-2 [1] and UCF Sports [2] with human eye movements collected under the ecological constraints of visual action and scene context recognition tasks. To our knowledge these are the first large human eye tracking datasets to be collected and made publicly available for video, vision.imar.ro/eyetracking (497,107 frames, each viewed by 19 subjects), unique in terms of their (a) large scale and computer vision relevance, (b) dynamic, video stimuli, (c) task control, as well as free-viewing. Second, we introduce novel dynamic consistency and alignment measures, which underline the remarkable stability of patterns of visual search among subjects. Third, we leverage the significant amount of collected data in order to pursue studies and build automatic, end-to-end trainable computer vision systems based on human eye movements. Our studies not only shed light on the differences between computer vision spatio-temporal interest point image sampling strategies and the human fixations, as well as their impact for visual recognition performance, but also demonstrate that human fixations can be accurately predicted, and when used in an end-to-end automatic system, leveraging some of the advanced computer vision practice, can lead to state of the art results.

Optimal and human eye movements to clustered low value cues to increase decision rewards during search

Rewards have important influences on the motor planning of primates and the firing of neurons coding visual information and action. When eye movements to a target are differentially rewarded across locations, primates execute saccades towards the possible target location with the highest expected value, a product of sensory evidence and potentially earned reward (saccade to maximum expected value model, sMEV). Yet, in the natural world eye movements are not directly rewarded. Their role is to gather information to support subsequent rewarded search decisions and actions. Less is known about the effects of decision rewards on saccades. We show that when varying the decision rewards across cued locations following visual search, humans can plan their eye movements to increase decision rewards. Critically, we report a scenario for which five of seven tested humans do not preferentially deploy saccades to the possible target location with the highest reward, a strategy which is optimal when rewarding eye movements. Instead, these humans make saccades towards lower value but clustered locations when this strategy optimizes decision rewards consistent with the preferences of an ideal Bayesian reward searcher that takes into account the visibility of the target across eccentricities. The ideal reward searcher can be approximated with a sMEV model with pooling of rewards from spatially clustered locations. We also find observers with systematic departures from the optimal strategy and inter-observer variability of eye movement plans. These deviations often reflect multiplicity of fixation strategies that lead to near optimal decision rewards but, for some observers, it relates to suboptimal choices in eye movement planning.

Bayesian Decision Theory Application for Double-step Saccades

Bayesian decision theory applied to the human saccadic eye movements elicited in double-step mode: primary and corrective saccade. Primary saccade performs large amplitude but not precise eye jump towards new target position and small amplitude corrective saccade brings line of sight precisely on the target. This behavior mach two-step Bayesian decision making process: first with large uncertainty and second, after getting additional information, – more precise. It explains how saccadic eye movements control system performs precise eye jump in the conditions of the noisy visual estimation of the new target position and eye jump errors made by eye globe muscles. Scatter of the landing places of the primary saccades was investigated theoretically using Bayesian statistics approach and experimentally. Ill. 5, bibl. 6 (in English; summaries in English, Russian and Lithuanian).

Saccadic model of eye movements for free-viewing condition

In this paper, we propose a new framework to predict visual scanpaths of observers while they freely watch a visual scene. The visual fixations are inferred from bottom-up saliency and several oculomotor biases. Bottom-up saliency is represented by a saliency map whereas the oculomotor biases (saccade amplitudes and saccade orientations) are modeled using public eye tracking datasets. Our experiments show that the simulated scanpaths exhibit similar trends of human eye movements in a free-viewing condition. The generated scanpaths are more similar to human scanpaths than those generated by two existing methods. In addition, we show that computing saliency maps from simulated visual scanpaths allows to outperform existing saliency models.

Infrared micro-scanning error compensation algorithm based on edge location

For area-array thermal imaging devices, an essential factor affecting the system imaging quality is the sub-sampling caused by oversized discrete sampling pitch. In order to obtain higher spatial resolution, staring infrared focal plane array (IRFPA) gets multi-frame sub-sampling images by micro-scanning movement to achieve an adequate spatial sampling frequency. However, influenced by external environment and the accuracy of the scanning system itself, the relative displacement between the detector and the scene cannot be absolutely precisely controlled, but exist some error, which will affect the final performance of the reconstructed high-resolution image. We analyzed the distribution of the error and then proposed an infrared micro-scanning error compensation algorithm based on edge location, which is inspired by human retina fixational eye movement pattern. It first locates the edge point in the reconstruction unit and finds the corresponding characteristic values. Later on, matches the characteristic value with the fixed templates and reorders the pixel responses in reconstruction unit utilizing the gray correlation. Finally, it compensates the error real-timely through repeated update and iteration. We apply the algorithm in video sequences acquired by 4-step infrared micro-scanning system. The experiment results show that when aligning to a static scene or stationary region in dynamic scene, the algorithm possesses good resolution enhancement effect, particularly, can improve the clarity and the accuracy of static image edge details.