• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.575-580
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• 2010

Eye gaze as a form of input was primarily developed for users who are unable to use usual interaction devices such as keyboard and the mouse; however, with the increasing accuracy in eye gaze detection with decreasing cost of development, it tends to be a practical interaction method for able-bodied users in soon future as well. This paper explores a low-cost, robust, rotation and illumination independent eye gaze system for gaze enhanced user interfaces. We introduce two brand-new algorithms for fast and sub-pixel precise pupil center detection and 2D Eye Gaze estimation by means of deformable template matching methodology. In this paper, we propose a new algorithm based on the deformable angular integral search algorithm based on minimum intensity value to localize eyeball (iris outer boundary) in gray scale eye region images. Basically, it finds the center of the pupil in order to use it in our second proposed algorithm which is about 2D eye gaze tracking. First, we detect the eye regions by means of Intel OpenCV AdaBoost Haar cascade classifiers and assign the approximate size of eyeball depending on the eye region size. Secondly, using DAISMI (Deformable Angular Integral Search by Minimum Intensity) algorithm, pupil center is detected. Then, by using the percentage of black pixels over eyeball circle area, we convert the image into binary (Black and white color) for being used in the next part: DTBGE (Deformable Template based 2D Gaze Estimation) algorithm. Finally, using DTBGE algorithm, initial pupil center coordinates are assigned and DTBGE creates new pupil center coordinates and estimates the final gaze directions and eyeball size. We have performed extensive experiments and achieved very encouraging results. Finally, we discuss the effectiveness of the proposed method through several experimental results.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.189-196
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• 2018

Player's actions in a game occur in the process of gameplay experiences in a play space designed by the developer according to preset gameplay beats. Focusing on beats that induce a first-person shooter (FPS) game's main gameplay, this paper analyzes the differences in eye gaze information found in different players during the course of gameplay. For this research goal, the study divides the beat areas in which play actions appear in association with gameplay beats at a typical FPS game level, repeatedly conducts tests in accordance with a player's experience level (novice and expert group), and collects and analyzes eye gaze information data in three types of beat areas. The analysis result suggests concrete guidelines for game level design for different beat areas based on an FPS game player's experience level. This empirical experiment method and result can lessen repetitive modification work for game level design and consequently be utilized for optimizing the game level to the developer's intention.

• Journal of the Korea Computer Graphics Society
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• v.24 no.1
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• pp.19-26
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• 2018

In this paper, we propose a gaze depth estimation method based on a binocular eye tracker for virtual reality and augmented reality applications. The proposed gaze depth estimation method collects a wide range information of each eye from the eye tracker such as the pupil center, gaze direction, inter pupil distance. It then builds gaze estimation models using Multilayer perceptron which infers gaze depth with respect to the eye tracking information. Finally, we evaluated the gaze depth estimation method with 13 participants in two ways: the performance based on their individual models and the performance based on the generalized model. Through the evaluation, we found that the proposed estimation method recognized gaze depth with 90.1% accuracy for 13 individual participants and with 89.7% accuracy for including all participants.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.11-19
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• 2016

The size of a display is large, The form becoming various of that do not apply to previous methods of gaze tracking and if setup gaze-track-camera above display, can solve the problem of size or height of display. However, This method can not use of infrared illumination information of reflected cornea using previous methods. In this paper, Robust pupil detecting method for eye's occlusion, corner point of inner eye and center of pupil, and using the face pose information proposes a method for calculating the simply position of the gaze. In the proposed method, capture the frame for gaze tracking that according to position of person transform camera mode of wide or narrow angle. If detect the face exist in field of view(FOV) in wide mode of camera, transform narrow mode of camera calculating position of face. The frame captured in narrow mode of camera include gaze direction information of person in long distance. The method for calculating the gaze direction consist of face pose estimation and gaze direction calculating step. Face pose estimation is estimated by mapping between feature point of detected face and 3D model. To calculate gaze direction the first, perform ellipse detect using splitting from iris edge information of pupil and if occlusion of pupil, estimate position of pupil with deformable template. Then using center of pupil and corner point of inner eye, face pose information calculate gaze position at display. In the experiment, proposed gaze tracking algorithm in this paper solve the constraints that form of a display, to calculate effectively gaze direction of person in the long distance using single camera, demonstrate in experiments by distance.

• Journal of Digital Contents Society
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• v.5 no.3
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• pp.239-244
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• 2004

New developments in IT already impact wide segments of a young and mobile population. It is evident that applications of information technology can be of equal benefit to the aged and the disabled. `Eye-Gaze'(EGI) technology was designed for people with paralysis in the upper body. There is a compeling need for a dedicated Korean Language interface for this system. The purpose of this study is to research 'Barrier Free' software using a control group of the mobility impaired to assess the Eye-Gaze Interface in the context of more conventional input methods. TheEGI of this study uses Quick Glance System of Eye Tech Digital Systems. The study will be evaluated on criteria based upon the needs of those with specific disabilities and mobility problems associated with aging. We also intend to explore applications of the Eye-Gaze Interface for English and Japanese devises, based upon our study using the Hangul phonology.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.84-88
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• 2005

Eye gaze positions evaluation on computer screen uses the human eye as an input device for computer systems is that it gives low resolution. We proposes a method to determine the eye gaze positions on the screen by using two-eye displacements as the information for mapping, and the perspective projection is applied to map the displacements to a position on a computer screen. The experiments were performed on 20 persons and a 17-inch monitor is used with the screen resolution of 1024x768 pixels. Gaze detection error was 3.18 cm (RMS error), with screen is divided into 5x8 and 7x10 positions on a 17-inch monitor. The results showed 100% and 96% correction, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.834-848
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• 2013

To effectively use these functions many kinds of human-phone interface are used such as touch, voice, and gesture. However, the most important touch interface cannot be used in case of hand disabled person or busy both hands. Although eye tracking is a superb human-computer interface method, it has not been applied to smartphones because of the small screen size, the frequently changing geometric position between the user's face and phone screen, and the low resolution of the frontal cameras. In this paper, a new eye tracking method is proposed to act as a smartphone user interface. To maximize eye image resolution, a zoom lens and three infrared LEDs are adopted. Our proposed method has following novelties. Firstly, appropriate camera specification and image resolution are analyzed in order to smartphone based gaze tracking method. Secondly, facial movement is allowable in case of one eye region is included in image. Thirdly, the proposed method can be operated in case of both landscape and portrait screen modes. Fourthly, only two LED reflective positions are used in order to calculate gaze position on the basis of 2D geometric relation between reflective rectangle and screen. Fifthly, a prototype mock-up design module is made in order to confirm feasibility for applying to actual smart-phone. Experimental results showed that the gaze estimation error was about 31 pixels at a screen resolution of $480{\times}800$ and the average hit ratio of a $5{\times}4$ icon grid was 94.6%.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.367-373
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• 2016

In this paper, we propose a novel method to improve the accuracy of eye trackers and how to analyze them. The proposed method extracts a user profile information created by extracting gaze coordinates and color information based on the exact pupil information, and then, it maintains a high accuracy in the display. In case that extract the user profile information, the changes of the accuracy for the gaze time also is estimated and the optimum parameter value is extracted. In the experimental results for the accuracy of the gaze detection, the accuracy was low if a user took a short time in a specific point. On the other hand, when taking more than two seconds, the accuracy was measured more than 80 %.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12C
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• pp.1239-1249
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• 2003

Gaze detection is to locate the position on a monitor screen where a user is looking by computer vision. Previous gaze detection system uses a wide view camera, which can capture the whole face of user. However, the image resolution is too low with such a camera and the fine movements of user's eye cannot be exactly detected. So, we implement the gaze detection system with a wide view camera and a narrow view camera. In order to detect the position of user's eye changed by facial movements, the narrow view camera has the functionalities of auto focusing and auto pan/tilt based on the detected 3D facial feature positions. 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 3.1 cm of RMS error in case of Permitting facial movements and 3.57 cm in case of permitting facial and eye movement. The processing time is so short as to be implemented in real-time system(below 30 msec in Pentium -IV 1.8 GHz)

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.123-129
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• 2023

if we know what we're looking at, we can get a lot of information. Due to the development of eye tracking, Information on gaze point can be obtained through software provided by various eye tracking equipments. However, it is difficult to estimate accurate information such as the actual gaze depth. If it is possible to calibrate the eye tracker with the actual gaze depth, it will enable the derivation of realistic and accurate results with reliable validity in various fields such as simulation, digital twin, VR, and more. Therefore, in this paper, we experiment with acquiring and calibrating raw gaze depth using an eye tracker and software. The experiment involves designing a Deep Neural Network (DNN) model and then acquiring gaze depth values provided by the software for specified distances from 300mm to 10,000mm. The acquired data is trained through the designed DNN model and calibrated to correspond to the actual gaze depth. In our experiments with the calibrated model, we were able to achieve actual gaze depth values of 297mm, 904mm, 1,485mm, 2,005mm, 3,011mm, 4,021mm, 4,972mm, 6,027mm, 7,026mm, 8,043mm, 9,021mm, and 10,076mm for the specified distances from 300mm to 10,000mm.