眼睛影像追蹤之瞌睡警示系統

Abstract

近年來因駕駛員疲勞所引發之意外事故時有所聞，已成為政府及社會大眾最大的隱憂。本篇論文提出了一套非侵入式的瞌睡警示偵測演算法，只需以一般的攝影器材就能達到持續追蹤駕駛員眼部之資訊，進而利用連續眼部資訊判斷目前駕駛員的精神狀態。當駕駛員出現闔眼過久的情況時，將立即發佈瞌睡警示，以確保行車安全。系統主要由五個模組所構成，其中包含了臉部偵測、眼睛區塊偵測、眼睛區塊驗證、眼睛精確定位及瞌睡警示判別等模組。系統執行中又分為偵測及追蹤兩種模式，其中偵測模式包含膚色分割、眼睛區塊偵測、眼睛區塊SVD (singular value decomposition)驗證及眼睛精確定位，而追蹤模式則包含了眼睛區塊快速偵測、眼睛精確定位及瞌睡警示判別模組，強調能準確偵測瞳孔高度並快速判別眼睛開闔狀態。經實驗證明，本研究提出之方法能偵測瞌睡達99.32%。

For the past few years, accidents caused by fatigue driving have occurred frequently, which has become the most serious concern of the government and the society. This thesis proposes a set of non-intrusive algorithm as a sleepiness detector which is capable to determine drivers’ mental state by analyzing the driver’s eyes on recorded images. When system detects the driver's eyes close for a period of time, the alarm will be triggered immediately to ensure safe driving. The system includes five functions, Face Detection, Eye Region Detection, Eye Verification, Eye Location, and Drowsiness Justification. Two modes, detecting and tracking 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 such that the state of driver’s eyes can be noticed quickly by the system. From experimental result, it was found 99.32 percent of correct drowsiness detection is achieved using the proposed method.