• 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)

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.700-702
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• 2018

In this abstract, introduces a system that enables communication by tracking the pupils of Lou Gehrig's disease patients who are unable to move their bodies. Face and eye pupil tracking perform using OpenCV, and eye movement recognition and character selection by eye movement is obtained using Python. In this paper, you will use the webcams, track your eyes, determine eye movements based on the coordinates of your pupils, and print characters that meet your preferences. It can easily output text messages using Bluetooth.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.205-208
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• 2005

본 논문은 특징 가중치 벡터를 적용하여 능동형태 모델(Active Shape Model)기반에서 눈동자의 움직임 추적 속도를 향상시키는 방법을 제안한다. 일반적인 능동형태 모델에서는 객체 추적을 위한 PDM 구성을 위해 각 특징점 구성 벡터의 유클리디안 거리의 최소 값으로 Training Set정렬 과정을 수행한다. 이 과정에서 적절하지 못한 샘플 영상으로 인해 안정된 PDM을 구성하지 못하는 문제점이 발생한다. 이러한 문제점을 해결하기 위하여 본 논문에 서는 형태를 구성하는 특징점마다 가중치를 부여하는 벡터를 작성하고, 최소자승근사법으로 최유사 특징점 벡터를 산출하기 위한 선형방정식을 구상하였다. 이로 인해 안정된 PDM을 구성할 수 있었으며, 눈동자 추적실험을 통해 형태적 움직임을 보정하는 실험을 수행하였다. 실험결과 기존의 능동형태 모델에 비해 반복연산의 횟수가 줄어들고, 다양한 형태로 나타나는 눈동자의 움직임 추적에 보다 안정적인 결과를 얻을 수 있었다.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.325-329
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• 2016

Facial authentication has the limelight because it has less resistance and it is hard to falsify among various biometric identification. The algorithm of facial authentication can bring about huge difference in accuracy and speed by the algorithm construction. Along with face-extracted data by tracing and extracting pupil, the thesis studied algorithm which extracts data to improve error rate and to accurately authenticate face. It detects face by cascade, selects as significant area, divides the facial area into 4 equal parts to save the coordinate of object. Also, to detect pupil from the eye, the binarization is conducted and it detects pupil by Hough conversion. The core coordinate of detected pupil is saved and calculated to conduct facial authentication through data matching. The thesis studied optimized facial authentication algorithm which accurately calculates facial data with pupil trace.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.696-699
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• 2018

This paper introduces a system that enables pupillary tracing and communication with patients with amyotrophic lateral sclerosis (ALS) who can not move free. Face and pupil are tracked using OpenCV, and eye movements are detected using DE1-SoC board. We use the webcam, track the pupil, identify the pupil's movement according to the pupil coordinate value, and select the character according to the user's intention. We propose a system that can use relatively low development cost and FPGA can be reusable, and can select a text easily to mobile phone by using Bluetooth.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.249-252
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• 2005

본 논문에서는 자동차를 운전 시에 운전자의 얼굴과 눈의 영역을 자동으로 검출하고 눈동자를 추적하여 운전자의 졸음 여부를 판단하는 효과적인 시스템 구현방법을 제안한다. 복잡한 배경에서 얼굴과 눈을 검출하는 방법은 Haar-like feature의 원리를 이용하고 졸음운전으로 판단하는 방법은 눈동자 영역의 특성과 눈동자의 검출 유무, 움직임 등의 인식을 통하여 졸음운전 경보시스템의 실용화에 대한 가능성을 확인한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1849-1856
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• 2012

This paper proposes a method to track the center of pupil and perform the remote control for interface based on the substituted commands according to movements of pupil under smart phone environment. The proposed method, which is a remote control through the movement of eyes, may be helpful for the handicapped people or users who want a more convenient input method. A method based on webcam, which is representative one among the previous methods to track pupil of user, has a few limitations on distance and angle between location of user and webcam. However, this paper uses smart phone that is convenient to carry. The proposed method can perform the remote control through tracking of pupil using wireless network without any restriction on the location of users. Thus, the method is effectively applied for controlling the smart TV that should be controlled on the distance as well as the remote control for PC.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.703-704
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• 2018

An artificial neural network design that traces the pupil for the disables suffering from Lou Gehrig disease is introduced. It grasps the position of the pupil required for the communication system. Tensorflow is used for generating and learning the neural network, and the pupil position is determined through the learned neural network. Convolution neural network(CNN) which consists of 2 stages of convolution layer and 2 layers of complete connection layer is implemented for the system.

• 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.

• Annual Conference of KIPS
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• 2006.11a
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• pp.113-116
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• 2006

컴퓨터의 급속한 발전 속도와 맞물려 사용자의 위지나 몸짓, 감성을 인지하는 보다 편리하고 자연스러운 휴먼 인터페이스에 대한 요구가 늘어나고 있다. 휴면 인터페이스 가운데 응시 위치 추적은 현재 사용자가 쳐다보고 있는 위치를 컴퓨터 시각 인식 방법을 통하여 파악하는 연구이다. 본 논문에서는 여러 감성 컴퓨터 인터페이스 중 눈동자를 통해 컴퓨터의 입력장치를 간접적으로 제어하는 방법에 대해 기술한다. 웹 카메라를 통해 입력 받은 영상을 이용하여 눈동자의 위치 이동을 탐색하여 마우스를 제어한다.