• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1340-1343
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• 1996

In this study, we developed the drowziness prevention system to detect the driver's drowziness and relieve the driver. A computer vision method was proposed to detect the driver's drowziness. We extracted the eyes and mouth in the face image and tracked the positions from the image sequencies in real time. The eye blink duration and yawning was used as the parameters of drowziness. Wehn the drowziness state of a driver is detected, the driver is refreshed by the scent generator and the alarm. Also, the driver's bio-signal is acquired and analysed the vigilance state.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.609-616
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• 2012

Objective: The aim of the study is to evaluate the difference of legibility between e-book and paper-book by using eye-tracker. Background: Despite of many researches on the e-book and paper-book, there are few researches on the difference between e-book and paper-book. In addition, the researches on the e-book were only dependent on the e-book reader. This study focused on the comparison of e-book and paper-book controlled with the same environments. Method: This study was conducted with $2{\times}3$ within-subject design. Independent variables include the types of book (e-book, paper-book) and font sizes (8pt, 10pt, 12pt). Dependent variables are four measures of fixation duration, saccade length, blink rate and subjective discomfort. Analysis of Variance (ANOVA) with repeated measured design was used to investigate the main and interaction effects of independent variables on each of the dependent variables. The multiple comparisons were performed by post hoc analysis and Bonferroni correction was applied. Results: Fixation duration at e-book was longer than paper-book (p<0.01). Saccade length at e-book was shorter than paper-book (p<0.05). Blink rate at e-book was higher than paper-book (p<0.1). Subjective discomfort at e-book was higher than paper-book (p<0.1). Legibility at 8pt was better than 10pt, 12pt (p<0.01) in fixation duration, saccade length and subjective discomfort. Conclusion: It was found that the legibility at e-book are worse than paper-book from this study. These results indicated that the legibility of e-book was needed to be validated and improved to replace the paper-book. Application: This study suggests improving something related to fixation duration, saccade length, blink rate and subjective discomfort for betterment of e-book.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.56-59
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• 1996

The purpose of this study is to identify the cause of driver's drowsiness and to get information about driver's drowsiness from facial image using computer vision. We measured the driver's movements of a head and shoulders in the highway arid street. We also measured the eye blink duration and yawning duration of normal and drowsy drivers. from the results, we confirmed that the measurement of eye blink and yawning might be a way of drowsy detection.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.463-471
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• 2014

In this paper, emotion classification was performed by using four ocular features extracted from near-infrared camera image. According to comparing with previous work, the proposed method used more ocular features and each feature was validated as significant one in terms of emotion classification. To minimize side effects on ocular features caused by using visual stimuli, auditory stimuli for causing two opposite emotion pairs such as "positive-negative" and "arousal-relaxation" were used. As four features for emotion classification, pupil size, pupil accommodation rate, blink frequency, and eye cloased duration were adopted which could be automatically extracted by using lab-made image processing software. At result, pupil accommodation rate and blink frequency were statistically significant features for classification arousal-relaxation. Also, eye closed duration was the most significant feature for classification positive-negative.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.45-50
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• 2021

This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the drowsy driving study, 10 drivers drove approximately 37 km of a monotonous highway (about 22 min) twice. The results suggested that the appropriate duration of eyes continuously closed was 4 seconds. The results from real-world driving data were presented in the other paper - part 1.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.1
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• pp.38-48
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• 2018

The purpose of this study is to improve the understanding of visual perception and to extend the landscape evaluation area by comparing eye-tracking evaluation and landscape adjective evaluation methods towards various type of nightscapes. As a result of the study, it showed that 'blink count', 'fixation duration average', and 'saccade duration average' of eye tracking measurements have a significant correlation with 'beautiful', 'interesting', 'accessible', 'satisfying', and 'safe' regarding landscape adjectives. In addition, there was a tendency toward areas of interests (AOIs) depending on 12 different nightscapes, which showed that the gaze was fixated by focusing on certain landscape elements such as 'door' and 'signs'. These results suggest that the eye-tracking method is an effective tool to specify the evaluation of 'landscape elements' rather than the 'whole landscape' and can be used as a basis to support landscape preference theories, which has been presented as conceptual only. In this way, the results of this study demonstrated the possibility of various applications of eye tracking as an objective landscape evaluation technique, and it is possible to suggest specific implications to landscape planning through the accumulation of continuous research results.

• Journal of Korean Elementary Science Education
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• v.32 no.2
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• pp.185-197
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• 2013

The purpose of this study was to analyze the difference between eye movements according to science achievement of elementary school students in observation situation. Science achievement was based on the results of national achievement test conducted in 2012, a random sampling of classes. As an assessment tool to check observation test, two observation measure problems from TSPS (Test of Science Process Skill; developed in 1994) suitable for eye tracking system are adopted. The subjects of this study were twenty students of sixth grade who agreed to participate in the research. SMI (SensoMotoric Instruments)' iView $X^{TM}$ RED was used to collect eye movement data and Experiment 3.1 and BeGaze 3.1 program were used to plan and analyze experiment. As a result, eye movements in observation test varied greatly in fixation duration, frequency, saccade, saccade velocity and eye blink according to students' science achievement. Based on the result of eye movements analysis, heuristic search eye movement was discussed as an alternative to improve underachievers' science achievement.

• Journal of Auto-vehicle Safety Association
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• v.13 no.1
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• pp.38-44
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• 2021

This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the real-world driving study, 52 drivers drove approximately 11.0 km of rural road (about 20 min), 7.9 km of urban road (about 25 min), and 20.8 km of highway (about 20 min). The results suggested that the appropriate number of blinks during the last 60 seconds was 4 times, and the head movement interval was 35 seconds. The results from drowsy driving data will be presented in another paper - part 2.

• 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.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.90-94
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• 1996

We studied the problem of driver's low vigilance state which is related to the one reason of traffic accidents. In this paper, we developed the drowsiness warning system for a drowsy driver. To extract the eyes and mouth from the driver's facial image in real time, a computer vision method was used. The eye blink duration and yawning were used as measurement parameters of drowsiness detection. When the drowsy state of a driver was detected, the driver was refreshed by the scent generator and the alarm. Also, the driver's bio-signal was acquired and analyzed to measure the vigilance state.