• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.91-100
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• 2009

In this paper, we propose autonomous intelligent wheelchair system which recognize the commands using the gaze recognition and avoid the detected obstacles by sensing the distance through range sensors on the way to driving. The user's commands are recognized by the gaze recognizer which use a centroid of eye pupil and two reflection points extracted using a camera with infrared filter and two infrared LEDs. These are used to control the wheelchair through the user interface. Then wheelchair system detects the obstacles using 10 ultrasonic sensors and assists that it avoid collision with obstacles. The proposed intelligent wheelchair system consists of gaze recognizor, autonomous driving module, sensor control board and motor control board. The gaze recognizer cognize user's commands through user interface, then the wheelchair is controled by the motor control board using recognized commands. Thereafter obstacle information detected by ultrasonic sensors is transferred to the sensor control board, and this transferred to the autonomous driving module. In the autonomous driving module, the obstacles are detected. For generating commands to avoid these obstacles, there are transferred to the motor control board. The experimental results confirmed that the proposed system can improve the efficiency of obstacle avoidance and provide the convenient user interface to user.

• 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 Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1162-1170
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• 2014

In this paper, an accurate remote gaze tracking method with two cameras is presented using a modified Starburst algorithm and honography normalization. Starburst algorithm, which was originally developed for head-mounted systems, often fails in detecting accurate pupil centers in remote tracking systems with a larger field of view due to lots of noises. A region of interest area for pupil is found using template matching, and then only within this area Starburst algorithm is applied to yield pupil boundary candidate points. These are used in improved RANSAC ellipse fitting to produce the pupil center. For gaze estimation robust to head movement, an improved homography normalization using four LEDs and calibration based on high order polynomials is proposed. Finally, it is shown that accuracy and robustness of the system is improved using two cameras rather than one camera.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.963-971
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• 2016

This paper is a research of gaze analysis for measuring task switching behavior at multiple windows in GUI of windowing system. Previous methods that define area of interest for categorizing gaze had difficulties to define dynamic content that disappears or changes over time. On the other hand, this study suggests a new method to categorize gaze that defines Area of interest in a unit of window during the eye tracking experiment. In this paper, we constructed the conception of WOI(Window of Interest) in GUI of windowing system. Therefore, we developed a system using an eye tracker device and implemented a number of experiments. In addition, we analyzed the number of task switching and proportion of watched content. The method in the study comprehend from previous researches as it can measure and analyze the multi-tasking behaviors using multiple numbers of windows.

• Electronics and Telecommunications Trends
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• v.28 no.2
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• pp.38-49
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• 2013

본고에서는 무선랜 기반 근접인식(proximity awareness) 모바일 서비스 제공에 필요한 관련 기술 동향 및 표준현황을 정리한다. 특히 수많은 기기들이 산재하는 모바일 D2D(Device to Device) 통신환경에서 인접 장치 및 서비스 발견 과정에 사용자 개입을 최소화할 수 있도록 접속 대상을 보고 선택하는 방식의 시선통신(look-and-link)과 네트워크 계층의 접속 이전에 주변 디바이스에서 제공되는 서비스를 미리 파악하거나 간단한 정보를 송수신할 수 있는 무결합 메시징(preassociation messaging) 연구동향을 소개한다. 이러한 기술은 셀룰러 중심의 기존 모바일 서비스들과 차별성을 가지며 무선랜 기술을 활용하는 D2D 환경에서 근접인식 모바일 서비스를 활성화할 수 있는 핵심 요소기술로 이용될 것이다.

• 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.5 no.4
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• pp.399-405
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• 2010

In this paper, the movement faces the problem of the difficult points upon the gaze of the user that corrective action is needed to solve the identification system offers a new perspective. Using the Kalman filter using the position information of the current head position estimated the future. In order to determine the authenticity of the face features of the face structural element information and the processing time is relatively fast horizontal and vertical histogram analysis method to detect the elements of the face. and people grow and infrared bright pupil effect obtained by constructing a real-time pupil detection, tracking and pupil - geulrinteu vectors are extracted.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.175-181
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• 2017

In this paper, we describe a design and development of car HUD(Head-Up-Display) navigation system using a Raspberry Pi. Car drivers can't concentrate on driving due to the use of various electronic devices, especially the car navigation systems installed in the cars. Therefore, car accident caused by not concentrating on the driving views is one of the most common accident types. In order to prevent the problems, HUD technology is used to help the driver to secure front views, thereby to minimize the traffic accidents caused by neglecting forward views. In this research, we propose the design and development techniques of a HUD navigation system using Raspberry Pi, and we believe that the commerical use of HUD navigation will grately reduce the risk of many car accidents.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.3
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• pp.331-338
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• 2016

In this paper, we propose a GRNN(: Generalized Regression Neural Network) algorithms for new eyes and face recognition identification system to solve the points that need corrective action in accordance with the existing problems of facial movements gaze upon it difficult to identify the user and. Using a Kalman filter structural information elements of a face feature to determine the authenticity of the face was estimated future location using the location information of the current head and the treatment time is relatively fast horizontal and vertical elements of the face using a histogram analysis the detected. And the light obtained by configuring the infrared illuminator pupil effects in real-time detection of the pupil, the pupil tracking was - to extract the text print vector.