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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/46402完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 丁肇隆 | |
| dc.contributor.author | I-Ling Tsai | en |
| dc.contributor.author | 蔡依陵 | zh_TW |
| dc.date.accessioned | 2021-06-15T05:07:15Z | - |
| dc.date.available | 2012-07-30 | |
| dc.date.copyright | 2010-07-30 | |
| dc.date.issued | 2010 | |
| dc.date.submitted | 2010-07-25 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/46402 | - |
| dc.description.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%。 | zh_TW |
| dc.description.abstract | 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. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T05:07:15Z (GMT). No. of bitstreams: 1 ntu-99-R97525071-1.pdf: 3953640 bytes, checksum: 3f933fca19273df50dcc63f2c0419ca7 (MD5) Previous issue date: 2010 | en |
| dc.description.tableofcontents | 口試委員審定書 I
致謝 II 摘要 III ABSTRACT IV 論文目錄 V 圖目錄 VII 表目錄 X 第一章、緒論 1 1.1 研究動機與目的 1 1.2 相關研究 3 1.3 論文架構 9 第二章、臉部偵測 10 2.1 膚色分割模組 10 2.1.1 色彩空間介紹 10 2.1.2 膚色分割模組建構 12 2.2 臉部偵測流程 14 2.2.1 膚色色彩分割 15 2.2.2 人臉範圍擷取與調整 17 第三章、眼睛區塊偵測與驗證 18 3.1 眼睛區塊偵測 18 3.1.1 眼睛區塊偵測前處理 19 3.1.2 視窗區塊大小的制定 20 3.1.3 利用視窗來搜尋眼睛區塊 24 3.1.4 區塊邊界修正與座標轉換 28 3.2 雙模式偵測 30 3.3 眼睛區塊驗證 32 3.3.1 SVD介紹 33 3.3.2 眼睛區塊分類法 37 第四章、眼睛定位與瞌睡警示 42 4.1 眼睛定位 42 4.1.1 眼睛區塊二值化 42 4.1.2 定位演算法 47 4.2 瞌睡警示 50 4.2.1 眼睛狀態之判斷 51 4.2.2 瞌睡偵測演算法 54 第五章、實驗結果與討論 56 5.1 裝備設置與規格 57 5.2 系統流程 57 5.3 實驗結果與討論 59 第六章、結論與未來方向 69 參考文獻 70 | |
| dc.language.iso | zh-TW | |
| dc.title | 眼睛影像追蹤之瞌睡警示系統 | zh_TW |
| dc.title | Sleepy Warning System by Tracking Human Eyes on Images | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 張瑞益 | |
| dc.contributor.oralexamcommittee | 黃乾綱,王家輝 | |
| dc.subject.keyword | 瞌睡偵測,疲勞偵測,臉部偵測,眼睛定位,SVD驗證, | zh_TW |
| dc.subject.keyword | Fatigue Detection,Drowsiness Detection,Face Detection,Eye Location,SVD Verification, | en |
| dc.relation.page | 74 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2010-07-27 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工程科學及海洋工程學研究所 | zh_TW |
| 顯示於系所單位： | 工程科學及海洋工程學系 | |
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| ntu-99-1.pdf 目前未授權公開取用 | 3.86 MB | Adobe PDF |
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