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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/68775

    Title: 利用光流與加速穩健特徵作車輛距離估測;Vehicle Distance Estimation Using Optical Flow and Speed Up Robust Feature
    Authors: 梁振浩;Liang,Cheng-hao
    Contributors: 資訊工程學系
    Keywords: 車輛偵測;陰影;車道線;光流;SURF;vehicle detection;shadow;lane;optical flow;SURF
    Date: 2015-07-24
    Issue Date: 2015-09-23 14:25:44 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 因高速公路的事故率日益嚴重的影響,使得車輛防碰撞系統為目前各個車廠積極地開發的趨勢,不僅如此,目前車輛防碰撞系統也被廣泛應用在無人駕駛車上,例如Apple、Benz、BMW、Audi等等開發廠商中,以 Google全自動駕駛汽車為具代表性。
    ;Because effect of accident rate rising on the highway, making vehicle anti-collision system as the current main trends. Moreover, currently vehicle anti-collision system is also widely used in unmanned aerial vehicles. Such as Apple, Benz, BMW, Audi, etc. Among Google Driverless Car as a representative.
    In recent years, most of the vehicle anti-collision system with sensors to prevent collisions. The reason the current prices of sensors are still expensive and the consumer demand of people is not high. Then, making low-cost vehicle anti-collision system to be vendors essential considerations.
    The purpose of the paper is to use single camera without assisting sensors to detect vehicle. Then, both symmetric line and the bottom of vehicle are met condition as vehicle. After getting the location of vehicle, we can use the information of vehicle and look-up table to convert the real distance. And then we can determine whether the forward vehicle is too close. By using both the strong direction of optical flow and the information of lane detected, we can determine whether vehicle departure lane and the near vehicle quickly drive to own lane. Then, if is true to alert driver. Avoiding accident to ensure safety of driver.
    Three different experiments were conducted to verify the validity of our proposed method. They were categorized in terms of candidate vehicle detection, candidate vehicle filter and judge, vehicle tracking. Experimental results demonstrate that the proposed method exhibit better detection rate.
    Appears in Collections:[資訊工程研究所] 博碩士論文

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