Early detection of mild cognitive impairment (MCI) is an important challenge in aging societies. Electroencephalography (EEG) and eye-tracking have independently been explored as potential biomarkers; however, their integrative effects remain insufficiently examined. This exploratory study investigated whether combining EEG spectral features with gaze variability may provide complementary information for MCI discrimination. EEG signals were recorded using the 10–20 system, and spectral power features were extracted. We compared three models: (a) high-dimensional EEG features, (b) L1-regularized feature selection (LASSO), and (c) integration of the selected EEG features with gaze variability. Performance was evaluated using leave-one-out cross-validation and area under the ROC curve (AUC). Model (a) yielded limited discrimination (AUC = 0.52). Feature selection increased AUC (0.64), and additional integration of gaze variability further increased AUC (0.78). These preliminary findings suggest potential complementarity between neural and behavioral variability measures.

Traditional authentication methods, such as biometrics and passwords, cannot guarantee security once the authenticated user changes after login. Periodic re-authentication at short intervals could preserve security but would severely degrade usability. To balance security and usability, we propose an implicit and continuous identification method based on eye-tracking data. Our approach compares a saliency map personalized for the legitimate user with the gaze heatmap of the current user, and identifies the current user as legitimate if the two maps are similar. To demonstrate our approach, we first develop and verify that a personalized saliency map well expresses a legitimate user’s gaze behavior. With one example result of the user study, we then illustrated the potential application of our identification as a second-factor authentication and as an unobtrusive re-authentication suggestion.

We release an eye-tracking dataset recorded with a Tobii Pro Fusion eye tracker (120 Hz) across six tasks: (1) repeated free viewing of 100 images over three sessions (300 presentations per participant), (2) gaze-pattern authentication, (3) numeric password entry, and (4-6) three 10-minute naturalistic screen activities (shopping, news browsing, and video viewing). Our key design choice is to present the same 100 images three times to obtain stable, participant-level average gaze behavior; the image order is deterministically randomized with a fixed seed such that all participants view the same sequence. Due to copyright restrictions, we provide only the 80 copyright-free natural images collected from the internet as stimuli. The dataset is released under the CC BY 4.0 license. We do not include baseline models or benchmark evaluations, allowing researchers to apply their own post-processing and modeling approaches to the unconstrained, raw tabular data.

The increasing prevalence of Alzheimer’s disease (AD) highlights the need for efficient and early detection. However, traditional cognitive assessments, such as the Mini-Mental State Examination (MMSE), which are administered in person, may not capture subtle early stage impairments. Recent studies have suggested that eye movements can serve as a biomarker for AD. In this study, we examined the use of dynamic time warping (DTW) to analyze smooth-pursuit eye movements to detect cognitive decline in 24 elderly participants, of whom 18 had valid eye tracking data for analysis. DTW was chosen because of its ability to capture the temporal alignment between the target and gaze trajectories. DTW demonstrated a stronger correlation with the MMSE scores (R = -0.782 and R 2 = 0.612) than with the conventional Pearson correlation coefficient (R = 0.456 and R 2 = 0.208). These findings highlight the potential of DTW-based analyses to complement existing cognitive screening tools in clinical settings. Future research should expand the participant pool and explore different smooth-pursuit paradigms to improve the predictive accuracy.

This poster presents a study on detecting Alzheimer’s disease (AD) using deep learning from gaze data. In this study, we modify an existing pre-trained deep neural network model, gazeNet, for transfer learning. The results suggest the possibility of applying this method to mild cognitive impairment screening tests.

Early detection of Alzheimer’s disease (AD) is important but difficult. Screening for AD using neuropsychological tests such as mini-mental state examination (MMSE) is time-consuming and burdensome for patients. Recently, several methods have been reported for detecting AD based on eye movements. However, analyzing eye movements requires considerable effort. Although machine learning from eye movement data is a strong candidate for labor-saving, it requires large datasets. In this study, we modify an existing pre-trained deep neural network model, gazeNet, for transfer learning. For evaluation, we exclusively used data from one participant and fine-tuned the model using data from all the remaining participants. We repeated this procedure separately for each of the 14 participants. The results of eye movement during the antisaccade task were not satisfactory for the discrimination of AD, and detailed analysis suggested that the data might potentially have a correlation with MMSE scores in the mild cognitive impairment range.

In recent studies on gaze tracking systems using 3D model-based methods, the optical axis of the eye was estimated without user calibration. The remaining challenge in achieving implicit user calibration is estimating the difference between the optical and visual axes of the eye (angle κ). In this study, we propose two methods that improve the implicit user calibration method using saliency maps, focusing on eye movement to reduce calculation costs while maintaining accuracy.

Several technical issues that affect eye-tracking have arisen concomitantly with the steadily increasing sizes of personal displays recently. One such issue is the loss of the illumination reflection of the near-infrared light-emitting diodes used as reference points around the edge of the display. Another issue is that reference identification is required for practical usage. Therefore, this paper proposes gaze estimation with transparent markers for large display environments to solve these problems. The transparent markers can be distributed on the screen, and a unique ID is assigned to each marker using linear polarization angles. The reference is detected using a polarization camera through the reflection on the cornea. The results of experiments conducted using a 50-inch display indicate that the proposed method can estimate the point-of-gaze to within 2.1 degrees of error. We confirmed that on-screen markers in sizable displays could be effectively used as references instead of illumination sources.

Eye tracking, which measures line of sight, is expected to advance as an intuitive and rapid input method for user interfaces, and a cross-ratio based method that calculates the point-of-gaze using homography matrices has attracted attention because it does not require hardware calibration to determine the geometric relationship between an eye camera and a screen. However, this method requires near-infrared (NIR) light-emitting diodes (LEDs) attached to the display in order to detect screen corners. Consequently, LEDs must be installed around the display to estimate the point-of-gaze. Without these requirements, cross-ratio based gaze estimation can be distributed smoothly. Therefore, we propose the use of a polarization camera for detecting the screen area reflected on a corneal surface. The reflection area of display light is easily detected by the polarized image because the light radiated from the display is polarized linearly by the internal polarization filter. With the proposed method, the screen corners can be determined without using NIR LEDs, and the point-of-gaze can be estimated using the detected corners on the corneal surface. We investigated the accuracy of the estimated point-of-gaze based on a cross-ratio method under various illumination and display conditions. Cross-ratio based gaze estimation is expected to be utilized widely in commercial products because the proposed method does not require infrared light sources at display corners.

A 3D gaze-tracking method that uses two cameras and two light sources can measure the optical axis of the eye without user calibration. The visual axis of the eye (line of sight) is estimated by conducting a single-point user calibration. This single-point user calibration estimates the angle k that is offset between the optical and visual axes of the eye, which is a user-dependent parameter. We have proposed an implicit user calibration method for gaze-tracking systems using a saliency map around the optical axis of the eye. We assume that the peak of the average of the saliency maps indicates the visual axis of the eye in the eye coordinate system. We used both-eye restrictions effectively. The experimental result shows that the proposed system could estimate angle k without explicit personal calibration.

Capturing Purkinje images is essential for wide-range and accurate eye-tracking. The range of eye rotation over which the Purkinje image is observable has so far been modeled by a cone shape called a gaze cone. In this study, we extended the gaze cone model to include occlusion by an eyelid. First, we developed a measurement device that has eight spider-like arms. Then, we proposed a novel model that considers eyeball movement. Using the device, we measured the range of corneal reflection, and we fitted the proposed model to the results.

Eye-based interaction is one of the solutions for achieving intuitive interfaces on surfaces such as a large display, and thus, various eye-tracking methods have been studied. Cross-ratio based gaze estimation, which determines the point-of-gaze on a screen, has been studied actively as a novel eye-tracking method because the method does not require a hardware calibration defining the relationship between a camera and monitor. We expect that the cross-ratio method will be a breakthrough for eye-based interaction under various circumstances such as tabletop devices and digital whiteboards. In eye-tracking, near-infrared light is often emitted, and at least four LEDs are located on display corners for detecting the screen plane in the cross-ratio based method. However, long-time radiation of near-infrared light can make a user fatigued. Therefore, in this study, we attempted to extract the screen area correctly without near-infrared radiation emission. A polarizing filter is included in the display, and thus, visibility of the screen can be controlled by the light's polarization direction of the external polarized light filter. We propose gaze estimation based on the cross-ratio method using a developed polarization camera system, which can capture two polarized images of different angles simultaneously. Further, we confirmed that the point-of-gaze could be estimated using the screen reflection detected by computing the differences between two images without near-infrared emission.

We propose a implicit calibration method for estimating the offset between the optical and visual axes without active participation of a user. The method relies on a fully calibrated setup and uses the relation between the optical axes of both eyes, the position of the center of the cornea, and the position of the display. The method is based on the assumption that the visual axes of both the eyes coincide on the display. The implicit calibration method estimates the offsets by continuously estimating the angle kappa through kernel density estimation. From the numerical simulation, the accuracy of our method is comparable or better than existing methods for implicit calibration.

In previous studies, the angle kappa, the offset between the optical axis and visual axis, was considered to be calibrated when eye trackers based on a 3D model were used. However, we found that the angle kappa could be used as personal information, which is immeasurable from outside the human body. This paper proposes a concept for PIN entry by considering the characteristics of the angle kappa. Thus, we measured the distribution of the angle kappa and developed a prototype of the system. We demonstrated the effectiveness of the method.

In this paper, we propose a mathematical model for a wide range gaze tracking system based on corneal reflections and pupil using calibrated stereo cameras and light sources. We demonstrate a general calculation method for estimating the optical axis of the eye for a combination of non-coaxial and coaxial configurations of many cameras and light sources. Gaze estimation is possible only when light is reflected from the spherical surface of the cornea. Moreover, we provide a method for calculating the eye rotation range where gaze tracking can be achieved, which is useful for positioning cameras and light sources in real world applications.

We developed and demonstrated the effectiveness of Hyakunin-Eyesshu, the world's first tabletop Hyakunin-Isshu game against a computer opponent that utilizes action prediction based on gaze and hand-motion detection. In this study, we also developed the gaze-and-touch algorithm, which can realize just-found and even-match timings for use in the computer opponent's play. The just-found timing is the timing for which the computer opponent can obtain a correct card concurrently with the reaction time of the player just after the player has found the card. The even-match timing is the timing for which the computer opponent obtains the card at almost the same time as the player by predicting the player's hand reach. Finally, the authors performed an experimental evaluation of the proposed algorithm and determined that various types of play can be realized through a combination of these timings.

A novel gaze estimation method based on a novel aspherical model of the cornea is proposed in this paper. The model is a surface of revolution about the optical axis of the eye. The calculation method is explained on the basis of the model. A prototype system for estimating the point of gaze (POG) has been developed using this method. The proposed method has been found to be more accurate than the gaze estimation method based on a spherical model of the cornea.

This paper presents a user-calibration-free method for estimating the point of gaze (POG) on a display accurately with estimation of the horizontal angles between the visual and the optical axes of both eyes. By using one pair of cameras and two light sources, the optical axis of the eye can be estimated. This estimation is carried out by using a spherical model of the cornea. The point of intersection of the optical axis of the eye with the display is termed POA. By detecting the POAs of both the eyes, the POG is approximately estimated as the midpoint of the line joining the POAs of both the eyes on the basis of the binocular eye model; therefore, we can estimate the horizontal angles between the visual and the optical axes of both the eyes without requiring user calibration. We have developed a prototype system based on this method using a 19" display with two pairs of stereo cameras. We evaluated the system experimentally with 20 subjects who were at a distance of 600 mm from the display. The result shows that the average of the root-mean-square error (RMSE) of measurement of POG in the display screen coordinate system is 16.55 mm (equivalent to less than 1.58°).

The intuitive user interfaces of PCs and PDAs, such as pen display and touch panel, have become widely used in recent times. In this study, we have developed an eye-tracking pen display based on the stereo bright pupil technique. First, the bright pupil camera was developed by examining the arrangement of cameras and LEDs for pen display. Next, the gaze estimation method was proposed for the stereo bright pupil camera, which enables one point calibration. Then, the prototype of the eye-tracking pen display was developed. The accuracy of the system was approximately 0.7° on average, which is sufficient for human interaction support. We also developed an eye-tracking tabletop as an application of the proposed stereo bright pupil technique.

This paper presents a one-point calibration gaze tracking method based on eyeball kinematics using stereo cameras. By using two cameras and two light sources, the optic axis of the eye can be estimated. One-point calibration is required to estimate the angle of the visual axis from the optic axis. The eyeball rotates with optic and visual axes based on the eyeball kinematics (Listing's law). Therefore, we introduced eyeball kinematics to the one-point calibration process in order to properly estimate the visual axis. The prototype system was developed and it was found that the accuracy was under 1° around the center and bottom of the display.

This paper presents a method to estimate the optic and visual axes of an eye and the Point Of Gaze (POG) on the bases of Listing’s law using stereo cameras for three-dimensional (3D) gaze tracking. By using two cameras and two light sources, the optic axis of the eye can be estimated on the basis of a spherical model of a cornea. A one-point calibration is required to estimate the angle of the visual axis from the optic axis. However, a real cornea has an aspheric shape and therefore it is difficult to estimate the POG in all the directions accurately. We have used three light sources to improve the estimation of the POG. Two light sources near the center of the pupil in the camera image are used for estimating the POG. The experimental results show that the accuracy of the estimation of the visual axis is under about 1°.

It is planned to install a front monitor impulse radar on the surface of the rotating drill of tunneling machines in order to detect obstacles such as casing pipes of vertical borings. The conventional aperture synthesis technique can no more be applied to such cases because the radar image of a pipe does not constitute a hyperbola as is the case for linear scanning radars. We have developed a special purpose signal processing algorithm with the aid of the discrete model fitting method, which can be used for any pattern of scanning. The details of the algorithm are presented together with the results of numerical simulations and test site experiments.