• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.601-607
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• 2012

Objective: The aim of this study is to classify between intentional and natural blinks in vision based eye tracking system. Through implementing the classification method, we expect that the great eye tracking method will be designed which will perform well both navigation and selection interactions. Background: Currently, eye tracking is widely used in order to increase immersion and interest of user by supporting natural user interface. Even though conventional eye tracking system is well focused on navigation interaction by tracking pupil movement, there is no breakthrough selection interaction method. Method: To determine classification threshold between intentional and natural blinks, we performed experiment by capturing eye images including intentional and natural blinks from 12 subjects. By analyzing successive eye images, two features such as eye closed duration and pupil size variation after eye open were collected. Then, the classification threshold was determined by performing SVM(Support Vector Machine) training. Results: Experimental results showed that the average detection accuracy of intentional blinks was 97.4% in wearable eye tracking system environments. Also, the detecting accuracy in non-wearable camera environment was 92.9% on the basis of the above used SVM classifier. Conclusion: By combining two features using SVM, we could implement the accurate selection interaction method in vision based eye tracking system. Application: The results of this research might help to improve efficiency and usability of vision based eye tracking method by supporting reliable selection interaction scheme.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.11-16
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• 2020

Deep Learning has become the most important technology in the field of artificial intelligence machine learning, with its high performance overwhelming existing methods in various applications. In this paper, an interactive window service based on object recognition technology is proposed. The main goal is to implement an object recognition technology using this deep learning technology to remove the existing eye tracking technology, which requires users to wear eye tracking devices themselves, and to implement an eye tracking technology that uses only usual cameras to track users' eye. We design an interactive system based on efficient eye detection and pupil tracking method that can verify the user's eye movement. To estimate the view-direction of user's eye, we initialize to make the reference (origin) coordinate. Then the view direction is estimated from the extracted eye pupils from the origin coordinate. Also, we propose a blink detection technique based on the eye apply ratio (EAR). With the extracted view direction and eye action, we provide some augmented information of interest without the existing complex and expensive eye-tracking systems with various service topics and situations. For verification, the user guiding service is implemented as a proto-type model with the school map to inform the location information of the desired location or building.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1111-1116
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• 2017

In this paper, we developed bio-signal based eye tracking system using electrooculogram (EOG) and electromyogram (EMG) which measured simultaneously from same electrodes. In this system, eye gazing position can be estimated using EOG signal and we can use EMG signal at the same time for additional command control interface. For EOG signal processing, PLA algorithms are applied to reduce processing complexity but still it can guarantee less than 0.2 seconds of reaction delay time. Also, we developed dual machine learning structure and it showed robust and enhanced tracking performances. Compare to conventional EOG based eye tracking system, developed system requires relatively light hardware system specification with only two skin contact electrodes on both sides of temples and it has advantages on application to mobile equipments or wearable devices. Developed system can provide a different UX for consumers and especially it would be helpful to disabled persons with application to orthotics for those of quadriplegia or communication tools for those of intellectual disabilities.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.91-98
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• 2019

The purpose of this study was to develop and test an eye tracker focusing on early childhood participants, based on the characteristics of early childhood eye tracking studies. Eye tracking collects eye movement data of the subject, which provides scientific evidence of human cognition and thinking. The researcher built a Do It Yourself eye tracker camera module from general electronic components, and used Viewpoint analysis software from Arrington Research. The researcher compared the eye tracking data between the DIY eye tracker group and Tobii Pro eye tracker group, which provides a professional eye tracking system. Eye tracking data was collected from 52 five-year old children. The average proportion of valid trials between the two groups was compared with t test, and no significant difference was found. This result indicates that the DIY eye tracker can be used to collect valid eye tracking data from young children under certain research environment.

• Smart Media Journal
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• v.10 no.1
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• pp.9-15
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• 2021

The eye tracking system designed in this paper is an eye-based computer input device designed to give an easy access for those who are uncomfortable with Lou Gehrig's or various muscle-related diseases. It is an eye-based-computer-using device for users whose potential demand alone amounts to 30,000. Combining the number of Lou Gehrig's patients in Korea estimated at around 1,700, and those who are unable to move their bodies due to various accidents or diseases. Because these eye input devices are intended for a small group of users, many types of commercial devices are available on the market. It is making them more expensive and difficult to use for these potential users, less accessible. For this reason, each individual's economic situation and individual experience with smart devices are slightly different. Therefore, making it difficult to access them in terms of cost or usability to use a commercial eye tracking system. Accordingly, attempts to improve accessibility to IT devices through low-cost but easy-to-use technologies are essential. Thus, this paper proposes a complementary superior performance eye tracking system that can be conveniently used by far more people and patients by improving the deficiencies of the existing system. Through voluntary VoCs(Voice of Customers) of users who have used different kinds of eye tracking systems that satisfies it through various usability tests, and we propose a reduced system that the amount of calculation to 1/15th, and eye-gaze tracking error rate to 0.5~1 degree under.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.33-35
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• 2005

We propose an eye gaze tracking system under natural head movements. The system consists of one CCD camera and two front-surface mirrors. The mirrors rotate to follow head movements in order to keep the eye within the view of the camera. However, the mirror controller cannot guarantee the fast head movements, because the frame rate is generally 30Hz. To overcome this problem, we applied Kalman predictor to estimate next eye position from the current eye image. In the results, our system allows the subjects head to move 50cm horizontally and 40cm vertically, with the speed about 10cm/sec and 6cm/sec, respectively. And spatial gaze resolutions are about 4.5 degree and 4.5 degree, respectively, and the gaze estimation accuracy is 92% under natural head movements.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.90-95
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• 2010

This paper describes the development of integrated head and eye tracker system. Vision based head tracker is performed and it has 7mm error in 300mm translation. The epi-polar method and point matching are used for determining a position of head and rotational degree. High brightness LEDs are installed on helmet and the installed pattern is very important to match the points of stereo system. Eye tracker also uses LED for constant illumination. A Position of gazed object(3m distance) is determined by pupil tracking and eye tracker has 1~5 pixel error. Integration of result data of each tracking system is important. RS-232C communication is applied to integrated system and triggering signal is used for synchronization.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.265-272
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• 2009

In this paper, a simple optical method that uses an infrared(IR) cut filter is proposed to minimize variation of eye image by external infrared(IR) sources in a video based head mounted eye tracking system that is used in the field of sports. For this, the IR cut filter is attached to a head mount of the eye tracking system, and the camera with an IR LED is located between the IR cut filter and eye. In this structure, external IR is blocked by the IR cut filter, and the IR intensity on the eye can be controlled by the IR LED. Therefore, the illumination condition of the camera to capture the eye can be stable without being affected by external IR illuminations. To verify the proposed idea, variation of the eye image and intensity of the IR with/without the IR cut filter is measured under various illumination conditions. The measured data show that the IR cut filter method can block external IR effectively, and complex pupil detection algorithms can be replaced by a simple binarized method.

• Journal of the Ergonomics Society of Korea
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• v.19 no.1
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• pp.77-90
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• 2000

The aim of this study is to develop and evaluate an efficient camera calibration method for vision-based head tracking. Tracking head movements is important in the design of an eye-controlled human/computer interface. A vision-based head tracking system was proposed to allow the user's head movements in the design of the eye-controlled human/computer interface. We proposed an efficient camera calibration method to track the 3D position and orientation of the user's head accurately. We also evaluated the performance of the proposed method. The experimental error analysis results showed that the proposed method can provide more accurate and stable pose (i.e. position and orientation) of the camera than the conventional direct linear transformation method which has been used in camera calibration. The results of this study can be applied to the tracking head movements related to the eye-controlled human/computer interface and the virtual reality technology.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.229-235
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• 2001

Recently, service area has been emerging field f robotic applications. Even though assistant robots play an important role for the disabled and the elderly, they still suffer from operating the robots using conventional interface devices such as joysticks or keyboards. In this paper we propose an efficient computer interface using real-time eye-gaze tracking system. The inputs to the proposed system are images taken by a camera and data from a magnetic sensor. The measured data is sufficient to describe the eye and head movement because the camera and the receiver of a magnetic sensor are stationary with respect to the head. So the proposed system can obtain the eye-gaze direction in spite of head movement as long as the distance between the system and the transmitter of a magnetic position sensor is within 2m. Experimental results show the validity of the proposed system in practical aspect and also verify the feasibility of the system as a new computer interface for the disabled.