English  |  正體中文  |  简体中文  |  Items with full text/Total items : 78852/78852 (100%)
Visitors : 37726988      Online Users : 525
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version

    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/9005

    Title: 行車安全偵測系統;An Attention Detection System for Vehicles
    Authors: 熊昭岳;Chao-Yueh Hsiung
    Contributors: 資訊工程研究所
    Date: 2005-07-04
    Issue Date: 2009-09-22 11:39:18 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 目前應用到車上的安全設備,大多都是在事故發生時,去保護駕駛人的生命安全,例如安全帶、安全氣囊等,如此消極的作法無法減少事故的發生。目前,已有許多研究者設計出各種車用安全系統,主要包含駕駛人疲勞偵測、行車狀態分析等,來偵測駕駛者安全與否。 基於上述論點,本論文提出一套行車安全偵測系統,此系統能偵測出駕駛人的行為及行車狀態,並能在事故發生前,有效的發出警告,如此一來,便可大幅地降低事故的發生。 本系統包含駕駛人注意力偵測及行車狀態分析兩個部份。在駕駛人注意力偵測部份,利用影像處理的技術,來找出眼睛及臉部中心的位置,由這三個特徵點所連結的三角形中三個邊的向量、三個夾角的資訊,去估算出駕駛者臉朝的方向。藉由人臉的偵測、三點特徵及人臉的朝向,我們可以定出一些規則來偵測駕駛人的注意力,例如眼睛偵測不到、眨眼頻率過高及頻繁地偏向別處等狀態。在行車狀態分析的部份,則是利用一個加速度感測器,此裝置可以同時測量兩個不同方向的加速度。將感測器架設在車上,記錄其因搖擺而輸出的數據,接著,我們使用有限狀態機去分析目前的行車狀態,在發覺行車狀態中有不當的駕駛行為時,有效的發出警告。它不僅僅可用於即時的偵測與警示,也可作為事後的推斷及分析,如此一來,我們可以在事後去觀察駕駛人不當的駕駛行為。最後,我們藉由實驗結果,證明了此系統在行車安全上之可行性及效能。 At present, there are many commercially available safety equipments such as the safety belts, airbags, etc, on vehicles. They are used to diminish the degree of injury while car accidents happen. These passive safety equipments can't really prevent the occurring of car accidents in practice. Recently, many various safety systems have been proposed. These safety systems concentrate on the driver fatigue detection, lane detection, etc. In this thesis, an attention detection system for vehicles is proposed to detect the driver’s driving behaviors and driving states while driving. Via the attention detection system warning signals will be issued in time when an accident is going to happen. In this way, car accidents can then be greatly reduced. There are two functional blocks in the attention detection system. They include the driver attention detection block and the driving state analysis block. In the driver attention detection block, a web camera is used to acquire driver’s images while driving. Some image processing techniques are utilized to locate the positions of eyes and the center of the face. These three feature points consist of a triangle. The three edge vectors and the three included angles in the triangle can then be used to estimate the driver’s face orientations. In addition to the information about the face orientations, information about the eye-closure frequency and the information about the appearance of the face are integrated to determine whether the driver’s attention degree. The driving state analysis block involves in the use of an accelerometer circuit. The accelerometer can measure the degree of the acceleration of two different directions at the same time. The accelerometer circuit will record the driving states of the car. Then a finite state machine is used to analyze the driving states. Signals can be issued in time to warn the driver while improper driving behaviors are detected. In fact, we can also use the driving state analysis block to determine how often a bus or truck driver exhibits improper driving behaviors after he or she completes a journey. Experiments were conducted to test the performance of the proposed attention detection system.
    Appears in Collections:[資訊工程研究所] 博碩士論文

    Files in This Item:

    File SizeFormat

    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明