• 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)

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.79-88
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• 2004

Gaze detection is to locate the position on a monitor screen where a user is looking by computer vision. Gaze detection systems have numerous fields of application. They are applicable to the man-machine interface for helping the handicapped to use computers and the view control in three dimensional simulation programs. 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 4.8 cm of RMS error.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.49-64
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• 2008

Recently, many researches about making more comfortable input device based on gaze detection technology have been done in human computer interface. However, the system cost becomes high due to the complicated hardware and there is difficulty to use the gaze detection system due to the complicated user calibration procedure. In this paper, we propose a new gaze detection method based on the 2D analysis and a simple user calibration. Our method used a small USB (Universal Serial Bus) camera attached on a HMD (Head-Mounted Display), hot-mirror and IR (Infra-Red) light illuminator. Because the HMD is moved according to user's facial movement, we can implement the gaze detection system of which performance is not affected by facial movement. In addition, we apply our gaze detection system to 3D first person shooting game. From that, the gaze direction of game character is controlled by our gaze detection method and it can target the enemy character and shoot, which can increase the immersion and interest of game. Experimental results showed that the game and gaze detection system could be operated at real-time speed in one desktop computer and we could obtain the gaze detection accuracy of 0.88 degrees. In addition, we could know our gaze detection technology could replace the conventional mouse in the 3D first person shooting game.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1228-1238
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• 2003

This paper presents a new and practical method based on computer vision for detecting the monitor position where the user is looking. In general, the user tends to move both his face and eyes in order to gaze at certain monitor position. Previous researches use only one wide view camera, which can capture a whole user's face. In such a case, the image resolution is too low and the fine movements of user's eye cannot be exactly detected. So, we implement the gaze detection system with dual camera systems(a wide and a narrow view camera). In order to locate the user's eye position accurately, the narrow view camera has the functionalities of auto focusing and auto panning/tilting based on the detected 3D facial feature positions from the wide view camera. In addition, we use dual R-LED illuminators in order to detect facial features and especially eye features. As experimental results, we can implement the real-time gaze detection system and the gaze position accuracy between the computed positions and the real ones is about 3.44 cm of RMS error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9C
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• pp.756-760
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• 2010

This paper is proposed to an novel facial behavior recognition system for driver's fatigue detection. Facial behavior is shown in various facial feature such as head expression, head pose, gaze, wrinkles. But it is very difficult to clearly discriminate a certain behavior by the obtained facial feature. Because, the behavior of a person is complicated and the face representing behavior is vague in providing enough information. The proposed system for facial behavior recognition first performs detection facial feature such as eye tracking, facial feature tracking, furrow detection, head orientation estimation, head motion detection and indicates the obtained feature by AU of FACS. On the basis of the obtained AU, it infers probability each state occur through Bayesian network.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.61-69
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• 2009

In this paper, to propose a new approach to real-time eye tracking. Existing methods of tracking the user's attention to the little I move my head was not going to get bad results for each of the users needed to perform the calibration process. Infrared eye tracking methods proposed lighting and Generalized Regression Neural Networks (GRNN) By using the calibration process, the movement of the head is large, even without the reliable and accurate eye tracking, mapping function was to enable each of the calibration process by the generalization can be omitted, did not participate in the study eye other users tracking was possible. Experimental results of facial movements that an average 90% of cases, other users on average 85% of the eye tracking results were shown.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.175-182
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• 2020

The non-contact eye tracking is a nonintrusive human-computer interface providing hands-free communications for people with severe disabilities. Recently. it is expected to do an important role in non-contact systems due to the recent coronavirus COVID-19, etc. This paper proposes a novel approach for an eye mouse using an eye tracking method based on a context-aware based AdaBoost multi-region classifier and ASSL algorithm. The conventional AdaBoost algorithm, however, cannot provide sufficiently reliable performance in face tracking for eye cursor pointing estimation, because it cannot take advantage of the spatial context relations among facial features. Therefore, we propose the eye-region context based AdaBoost multiple classifier for the efficient non-contact gaze tracking and mouse implementation. The proposed method detects, tracks, and aggregates various eye features to evaluate the gaze and adjusts active and semi-supervised learning based on the on-screen cursor. The proposed system has been successfully employed in eye location, and it can also be used to detect and track eye features. This system controls the computer cursor along the user's gaze and it was postprocessing by applying Gaussian modeling to prevent shaking during the real-time tracking using Kalman filter. In this system, target objects were randomly generated and the eye tracking performance was analyzed according to the Fits law in real time. It is expected that the utilization of non-contact interfaces.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.750-753
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• 2012

A method detecting the position of eyes and tracking a gaze point of eyes in realtime using POSIT is suggested in this paper. This algorithm find out a candidate area of eyes using topological characteristics of eyes and then decides the center of eyes using physical characteristics of eyes. To find the eyes, a nose and a mouth are used for POSIT. The experimental results show that proposed method effectively performed detection of eyes in facial image in FERET databases and gave high performance when used for tracking a gaze point of eyes.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.973-980
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• 2011

In this paper, we gaze upon the movement faces the problem points are difficult to identify a user based on points and that corrective action is needed to solve the identification system is proposed a new eye. Kalman filter, the current head of the location information was used to estimate the future position in order to determine the authenticity of the face facial features and structural elements, the information and the processing time is relatively fast horizontal and vertical elements of the face using the histogram analysis to detect. And an infrared illuminator obtained by constructing a bright pupil effect in real-time detection of the pupil, the pupil was tracked - geulrinteu vectors are extracted.