• 제목/요약/키워드: Eye-blink Detection

검색결과 15건 처리시간 0.031초

눈 깜박임 패턴을 이용한 졸음 검출 (Drowsiness Detection using Eye-blink Patterns)

  • 최기호
    • 한국ITS학회 논문지
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    • 제10권2호
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    • pp.94-102
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    • 2011
  • 본 논문은 눈 깜박임 패턴을 이용한 새로운 졸음 검출 알고리즘을 제안하였다. 유한오토마타를 이용한 졸음 검출 모델을 제안하여 눈감은 상태를 나타내는 입력 심벌의 개수만을 체크함으로써 눈 깜박임, 졸음, 수면 검출을 용이하게 하였다. 또한 수평 투영 히스토그램의 특성을 이용하여 눈동자가 있는 영역만을 구해 수직 투영 히스토그램을 취함으로써 눈썹이나 안경테와 같은 외부 영향을 최소화 시켜 정확도를 높였다. ZJU 눈 깜박임 데이터베이스를 이용한 눈 깜박임 검출 실험 결과 93% 이상의 정확도를 얻음으로써 제안된 방법의 우수함을 보였다.

라인 프로파일을 이용한 템플릿 매칭 기반의 운전자 눈 깜박임 검출 방법 (Driver's Eye Blinking Detection Method based on Template Matching using Line Profile)

  • 김영재;신승섭;김광기
    • 한국멀티미디어학회논문지
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    • 제20권6호
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    • pp.873-881
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    • 2017
  • Prevention of drowsy driving is one of the important issues for safe driving. In this study, the algorithm for detection of drowsy driving has been developed. The algorithm was implemented by applying template matching and line profile, which detects eye blink. The accuracy of eye detection and blink detection was $97.45{\pm}3.67%$ and $98.50{\pm}0.92%$, which was resulted from the verification experiment that 21 subjects participated. Consequently, the algorithm is expected to be used to prevent sleep-deprived driving.

비접촉 눈 깜박임 측정 안경형 디바이스를 이용한 실시간 스펠러의 구현 (Development of Online Speller using Non-contact Blink Detection Glasses)

  • 이정수;이홍지;이원규;임용규;박광석
    • 대한의용생체공학회:의공학회지
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    • 제36권6호
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    • pp.283-290
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    • 2015
  • We proposed blink based online speller for the locked-in syndrome (LIS) patients, paralyzed in nearly all voluntary muscles expect for the eyes, with a simple and easy-to-use eye blink detection glasses. Electrooculogram (EOG) is the golden standard method of eye movement or blink measurement with Ag/AgCl electrodes. However, this method has several drawbacks such as skin irritation and dehydration of conductive gel. To resolve the shortcomings, we used a blink detection system based on a transparent capacitively coupled electrode, which is conductive indium tin oxide (ITO) films. The films make it possible to measure eye blink without direct skin contact and obstruction of field of view. We finally developed user-friendly blink based online speller with the blink detection system. To classify voluntary and non-voluntary blink, we used the double blink for command of the speller. The online speller experiment result with six healthy subjects shows that mean accuracy is 98.96% and letter per minute (LPM) is 4.73, which are better result by comparison with conventional P300 or auditory brain-computer interface (BCI) paradigm. The result of the experiment demonstrates the possibility of applying the proposed system as a communication method for the LIS patients.

Drowsiness Sensing System by Detecting Eye-blink on Android based Smartphones

  • Vununu, Caleb;Seung, Teak-Young;Moon, Kwang-Seok;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • 한국멀티미디어학회논문지
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    • 제19권5호
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    • pp.797-807
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    • 2016
  • The discussion in this paper aims to introduce an approach to detect drowsiness with Android based smartphones using the OpenCV platform tools. OpenCV for Android actually provides powerful tools for real-time body's parts tracking. We discuss here about the maximization of the accuracy in real-time eye tracking. Then we try to develop an approach for detecting eye blink by analyzing the structure and color variations of human eyes. Finally, we introduce a time variable to capture drowsiness.

연속된 영상 프레임에서 눈의 깜빡임 해석 (Analysis of the Eye Blink in Video Sequences)

  • 차태환;김주영;고광식
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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    • pp.331-334
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    • 2000
  • This paper presents the method for the decision of eye states using the eye blink in video sequences. The entire procedure consists of two steps: in the first step, the accurate eye position is found in the input image by using symmetry information of faces and projection, and in the second step, the eye open/close state is decided by the horizontal and vertical projection. The method in this paper is also used for detecting drivers' fatigue in the drowsiness detection system.

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Eye Blink Detection and Alarm System to Reduce Symptoms of Computer Vision Syndrome

  • Atheer K. Alsaif;Abdul Rauf Baig
    • International Journal of Computer Science & Network Security
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    • 제23권5호
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    • pp.193-206
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    • 2023
  • In recent years, and with the increased adoption of digital transformation and spending long hours in front of these devices, clinicians have observed that the prolonged use of visual display units (VDUs) can result in a certain symptom complex, which has been defined as computer vision syndrome (CVS). This syndrome has been affected by many causes, such as light refractive errors, poor computer design, workplace ergonomics, and a highly demanding visual task. This research focuses on eliminating one of CVSs, which is the eye dry syndrome caused by infrequent eye blink rate while using a smart device for a long time. This research attempt to find a limitation on the current tools. In addition, exploring the other use cases to utilize the solution based on each vertical and needs.

졸음방지시스템 개발을 위한 졸음감지에 관한 연구 (A Study on the Drowsinss Detection for Development of Drowsiness Prevention System)

  • 정경호;김법중;김동욱;김남균
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1996년도 춘계학술대회
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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.

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졸음감지를 위한 깜박임 패턴 검출에 관한 연구 (A Study on the Blink Pattern Extraction of a Driver in Drowsy State)

  • 김법중;박상수;오승곤;김남균
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1997년도 춘계학술대회
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    • pp.322-325
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    • 1997
  • In this study, we propose a non-invasive method to detect the drowsiness of a driver. The computer vision technology was used to extract an eye, track eyelids and measure the parameters related to the blink. We examined the blink patterns of a driver in drowsy state. For the evaluation of our image processing algorithm, the blink patterns were compared with the measured EOG signals. The result showed that our algorithm might be available in detection of drowsiness.

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Development of Low-Cost Vision-based Eye Tracking Algorithm for Information Augmented Interactive System

  • Park, Seo-Jeon;Kim, Byung-Gyu
    • Journal of Multimedia Information System
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    • 제7권1호
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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.

Study of Eye Blinking to Improve Face Recognition for Screen Unlock on Mobile Devices

  • Chu, Chung-Hua;Feng, Yu-Kai
    • Journal of Electrical Engineering and Technology
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    • 제13권2호
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    • pp.953-960
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    • 2018
  • In recently, eye blink recognition, and face recognition are very popular and promising techniques. In some cases, people can use the photos and face masks to hack mobile security systems, so we propose an eye blinking detection, which finds eyes through the proportion of human face. The proposed method detects the movements of eyeball and the number of eye blinking to improve face recognition for screen unlock on the mobile devices. Experimental results show that our method is efficient and robust for the screen unlock on the mobile devices.