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題名:車輛主動式安全防護之瞌睡偵測與警示
書刊名:資訊、科技與社會學報
作者:蔡依陵丁肇隆張瑞益
作者(外文):Tsai, I-lingTing, Chao-lungChang, Ray-i
出版日期:2013
卷期:21
頁次:頁1-19
主題關鍵詞:瞌睡偵測車輛主動式安全防護臉部偵測眼睛定位Drowsy detectionVehicle active safetyFace detectionEye location
原始連結:連回原系統網址new window
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因人員瞌睡所引發之意外事故時有所聞,往往在交通安全上造成很大危害。本論文提出了一個駕駛員瞌睡偵測演算法,只需以一般的攝影與計算元件 (如:智慧手機)就能達到快速準確的持續追蹤人員眼部資訊,進而判斷駕駛員是否出現瞌睡或其他可能不正常駕駛的情況,發佈警示,以確保行車安全。整個系統主要分為兩個部分,其中偵測子系統負責在系統一開始時進行基本人臉定位,接著進入追蹤子系統來進行瞌睡警示判別。由於系統一開始時已完成基本定位,追蹤子系統可快速微調偵測驗證及定位眼睛區塊,再偵測瞳孔高度並判別眼睛開闔狀態以偵測瞌睡。系統只有在追蹤失敗一段時間後,才會回到偵測子系統重新進行基本人臉定位,所以正常情況下處理十分快速。而如果人臉偵測數次都失敗,很可能是在不正常駕駛的情況下所引起,系統也會發佈警示。經實驗證明,以目前智慧手機的 1GHz CPU及360*240攝影解析度,本系統偵測一張影像約需0.33秒,而追蹤一張影像約需0.07秒,其偵測瞌睡的正確率可達 99.32%。由於有偵測子系統所提供的正常眼睛開闔大小做參考,偵測瞌睡的假警報率很低,頗具有實用性。
Accidents caused by drowsy driving have occurred frequently, which has become the most serious concern of the government and the society. This paper proposes an non-intrusive drowsy driver detection algorithm which is capable to determine drivers' mental state by analyzing the driver's eyes. When system detects the driver's eyes close for a period of time, the alarm will be triggered to ensure safe driving. The system includes five functions: face detection, eye region detection, eye verification, eye location, and drowsiness justification. Two modes, detecting model and tracking model, are included during system operation. The detecting mode is used to locate driver's eyes at first time and verify the eyes are in the detected region. Once successful operation of the detecting mode is achieved, the system is switched to the tracking mode. By the continuous movement of eyes, a small region is searched and the eyes can be located quickly in the tracking mode. Therefore, using 1GHz CPU and 360*240 camera of a modern smart phone, the state of driver’s eyes can be detected in 0.33 second and tracked in 0.07 second. From our experimental results, the proposed system has 99.32% correctness in drowsiness detection is achieved using the proposed method.
期刊論文
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6.Patil, R. M.、Gajare, A. M.、Agrawal, D. G.(2012)。Drowsy driver detection system。Global Journal of Engg. & Appl. Sciences,2(1),90-93。  new window
7.Lee, B. G.、Chung, W. Y.(2012)。Multi-classifier for highly reliable driver drowsiness detection in Android platform。Journal of Biomedical Engineering,24(2),2012-147。  new window
8.Ji, Q.、Yang, X.(2002)。Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance。Real-Time Imaging,8(5),357-377。  new window
9.Eriksson, M.、Papanikolopoulos, N. P.(2001)。Driver fatigue: a vision-based approach to automatic diagnosis。Transportation Research Part C: Emerging Technologies,9(6),399-413。  new window
10.Soriano, M.、Martinkauppi, B.、Huovinen, S.、Laaksonen, M.(2003)。Adaptive skin color modeling using the skin locus for selecting training pixels。Pattern Recognition,36(3),681-690。  new window
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會議論文
1.Takei, Y.、Furukawa, Y.(2005)。Estimate of driver's fatigue through steering motion。IEEE International Conference on Systems, Man and Cybernetics,1765-1770。  new window
2.Popieul, J. C.、Simon, P.、Loslever, P.(2003)。Using driver's head movements evolution as a drowsiness indicator。IEEE Intelligent Vehicles Symposium,616-621。  new window
3.Wang, R.、Guo, L.、Tong, B.、Jin, L.(2004)。Monitoring mouth movement for driver fatigue or distraction with one camera。IEEE International Conference on Intelligent Transportation Systems,314-319。  new window
4.Wang, Q.、Yang, W.、Wang, H.、Guo, Z.、Yang, J.(2006)。Location in Face Images for Driver Fatigue Monitoring。International Conference on ITS Telecommunications,322-325。  new window
5.Wang, J.、Liu, B.(2009)。Design and Simulated Implementation of MATLAB-based Warning System for Fatigue Driving Driver。International Conference on Hybrid Intelligent Systems,467-470。  new window
6.Khairosfaizal, W. M.、Noraini, A. J.(2009)。Eyes Detection in Facial Images using Circular Hough Transform。International Colloquium on Signal Processing & Its Applications,238-242。  new window
7.Khan, M. I.、Mansoor, A. B.(2008)。Real Time Eyes Tracking and Classification for Driver Fatigue Detection。International conference on Image Analysis and Recognition,729-738。  new window
8.Zhang, Z.、Zhang, J.(2006)。A New Real-Time Eye Tracking for Driver Fatigue Detection。Internal Conference on ITS Telecommunications,8-11。  new window
9.Lang, L.、Qi, H.(2008)。The Study of Driver Fatigue Monitor Algorithm Combined PERCLOS and AECS。International Conference on Computer Science and Software Engineering,349-352。  new window
10.Grace, R.(2001)。Drowsy driver monitor and warning system。International Symposium on Human Factors in Driver Assessment, Training and Vehicle Design,64-69。  new window
11.Healey, J.、Picard, R.(2000)。SmartCar: detecting driver stress。15th International Conference on Pattern Recognition。Barcelona, Spain。218-221。  new window
12.Viola, P.、Jones, M.(2001)。Rapid Object Detection using a Boosted Cascade of Simple Features。IEEE Conference on Computer Vision and Pattern Recognition。Kauai, HI。511-518。  new window
學位論文
1.李濠欣(2009)。即時相機校正之前車偵測(碩士論文)。國立臺灣大學。  延伸查詢new window
2.Fan, K. W.(200709)。Smart Lateral Imaging for Driving Safety Supporting System(-)。National Chiao Tung University。  new window
3.Lin, C. S.(200710)。Electroencephalographic Spectral Changes from Alertness to Drowsiness in a Driving Simulator(碩士論文)。National Chiao Tung University。  new window
4.李硯農(2008)。Wii遊樂器之Mii頻道人像自動產生研究(碩士論文)。國立臺灣大學。  延伸查詢new window
5.Lin, S. M.(200706)。A Real-Time Driver Drowsiness Detection and Alertness Monitor System(碩士論文)。National Central University。  new window
 
 
 
 
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