• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.1
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• pp.38-46
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• 2010

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about $5^{\circ}$horizontally and $8^{\circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.322-329
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• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNS). With GRNNS, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10$\%$ improvement in classification error. The angular gaze accuracy is about $5^{circ}$horizontally and $8^{circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.37-54
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• 2010

The information system that preserves and presents information collections, records, processes, retrievals, is applied in various fields recently and is supporting man's many activities. Conventional information systems are based on the reactive interaction model. Such reactive systems respond to only specific instructions, i.e. the defined commands, from the user. To go beyond the reactive interaction, it is necessary that the interactive dynamic interaction based information system which understands human's action and intention autonomously and then provides sensible information adapted to the user. Therefore, we propose a Gaze Mirroring-based intelligent information system for making user's latent interest using the internal state estimation methods based on the interactive dynamic interaction. Then, the proposed Gaze Mirroring method is that an anthropomorphic agent(avatar) actively established the joint attention with the user by imitating user's eye-gaze behavior. We verify that the Gaze Mirroring can elicit the user's behavior reflecting the latent interestand contribute to improving the accuracy of interest estimation. We also have confidence that the Gaze Mirroring promotes the self-awareness of interest. Such a Gaze Mirroring-based intelligent information system also provides suitable information to user by making user's latent interest using the internal state estimation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.477-483
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• 2004

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks(GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Futhermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.512-517
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• 2007

There are several researches on 2D gaze tracking techniques for the 2D screen for the Human-Computer Interaction. However, the researches for the gaze-based interaction to the stereo images or contents are not reported. The 3D display techniques are emerging now for the reality service. Moreover, the 3D interaction techniques are much more needed in the 3D contents service environments. This paper addresses gaze-based 3D interaction techniques on stereo display, such as parallax barrier or lenticular stereo display. This paper presents our researches on 3D gaze estimation and gaze-based interaction to stereo display.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.857-861
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• 2004

This paper describes preliminary results we have obtained in developing a computer vision system based on active IR illumination for real time gaze tracking for interactive graphic display. Unlike most of the existing gaze tracking techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze tracker can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using the Generalized Regression Neural Networks (GRNN). With GRNN, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. The effectiveness of our gaze tracker is demonstrated by preliminary experiments that involve gaze-contingent interactive graphic display.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.431-440
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• 2006

There are several researches on 2D gaze tracking techniques for the 2D screen for the Human-Computer Interaction. However, the researches for the gaze-based interaction to the stereo images or contents are not reported. The 3D display techniques are emerging now for the reality service. Moreover, the 3D interaction techniques are much more needed in the 3D contents service environments. This paper addresses gaze-based 3D interaction techniques on stereo display, such as parallax barrier or lenticular stereo display. This paper presents our researches on 3D gaze estimation and gaze-based interaction to stereo display.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.494-504
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• 2004

The researches about gaze detection have been much developed with many applications. Most previous researches only rely on image processing algorithm, so they take much processing time and have many constraints. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.2 cm of RMS error.

• ETRI Journal
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• v.34 no.4
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• pp.542-552
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• 2012

In this paper, a gaze estimation method is proposed for use with a large-sized display at a distance. Our research has the following four novelties: this is the first study on gaze-tracking for large-sized displays and large Z (viewing) distances; our gaze-tracking accuracy is not affected by head movements since the proposed method tracks the head by using a near infrared camera and an infrared light-emitting diode; the threshold for local binarization of the pupil area is adaptively determined by using a p-tile method based on circular edge detection irrespective of the eyelid or eyelash shadows; and accurate gaze position is calculated by using two support vector regressions without complicated calibrations for the camera, display, and user's eyes, in which the gaze positions and head movements are used as feature values. The root mean square error of gaze detection is calculated as $0.79^{\circ}$ for a 30-inch screen.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.117-122
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• 2023

Gaze estimation, which automatically recognizes where a user is currently staring, and object detection based on estimated gaze point, can be a more accurate and efficient way to understand human visual behavior. in this paper, we propose a method to detect the objects within the region of interest around the gaze point. Specifically, after estimating the 3D gaze point, a region of interest based on the estimated gaze point is created to ensure that object detection occurs only within the region of interest. In our experiments, we compared the performance of general object detection, and the proposed object detection based on region of interest, and found that the processing time per frame was 1.4ms and 1.1ms, respectively, indicating that the proposed method was faster in terms of processing speed.