本文選題：事故車(chē)輛　切入點(diǎn)：城市視頻　出處：《長(zhǎng)安大學(xué)》2014年碩士論文

【摘要】：事故車(chē)輛的車(chē)速，作為事故鑒定中重要的一環(huán)，不僅能描述發(fā)生事故的性質(zhì)，還有利于對(duì)事故過(guò)程的重現(xiàn)。傳統(tǒng)的車(chē)速鑒定手段，通過(guò)獲取事故現(xiàn)場(chǎng)定位參數(shù)、事故痕跡、散落物等信息人工計(jì)算得出，不僅鑒定過(guò)程復(fù)雜，而且在一段時(shí)間內(nèi)降低了道路通行能力。因此，利用直觀(guān)、實(shí)時(shí)性好、對(duì)道路交通影響小的事故視頻進(jìn)行車(chē)速鑒定具有很強(qiáng)的運(yùn)用價(jià)值。 本文通過(guò)分析監(jiān)控?cái)z像頭標(biāo)定技術(shù)、運(yùn)動(dòng)目標(biāo)檢測(cè)與跟蹤技術(shù)的計(jì)算模型與計(jì)算步驟，提出了新的標(biāo)定方法與運(yùn)動(dòng)目標(biāo)(車(chē)輛)檢測(cè)、跟蹤過(guò)程，并通過(guò)VC++程序得以實(shí)現(xiàn)，建立了基于VC++的車(chē)速自動(dòng)化處理系統(tǒng)，最后通過(guò)實(shí)例完成系統(tǒng)實(shí)效性的檢驗(yàn)。 對(duì)監(jiān)控?cái)z像頭標(biāo)定方法進(jìn)行研究。分析了監(jiān)控?cái)z像頭標(biāo)定的線(xiàn)性方法與非線(xiàn)性方法的計(jì)算過(guò)程、模型與參數(shù)，提出了根據(jù)聚點(diǎn)及投影透視關(guān)系的一種簡(jiǎn)潔、穩(wěn)定的標(biāo)定方法，通過(guò)具體環(huán)境實(shí)驗(yàn)進(jìn)行精度校核。 對(duì)運(yùn)動(dòng)目標(biāo)(車(chē)輛)檢測(cè)技術(shù)以及跟蹤技術(shù)進(jìn)行研究。根據(jù)計(jì)算模型與計(jì)算方法的不同，分析了運(yùn)動(dòng)目標(biāo)(車(chē)輛)檢測(cè)中常用的光流法、幀間差法以及背景減法，，比較了多種技術(shù)的優(yōu)缺點(diǎn)，設(shè)計(jì)了運(yùn)用背景幀差模型與三圖像幀差模型相結(jié)合的車(chē)流體區(qū)域檢測(cè)模型。對(duì)提取后的目標(biāo)車(chē)輛運(yùn)動(dòng)中心進(jìn)行微元慣性運(yùn)動(dòng)分析，設(shè)計(jì)了車(chē)輛流體區(qū)域跟蹤模型。 開(kāi)發(fā)車(chē)速計(jì)算自動(dòng)化處理系統(tǒng)。以VC++為平臺(tái)，建立視頻圖像讀入與提取模塊，完成對(duì)視頻流的單幀圖像分離；依據(jù)實(shí)際路面參數(shù)，建立坐標(biāo)點(diǎn)映射關(guān)系以及空間坐標(biāo)系計(jì)算模塊；建立車(chē)流體區(qū)域定位模塊與跟蹤模塊，開(kāi)發(fā)出“事故車(chē)輛車(chē)速計(jì)算系統(tǒng)”，并通過(guò)實(shí)例完成系統(tǒng)實(shí)效性的檢驗(yàn)。
[Abstract]:As an important part of accident identification, the speed of vehicle is not only able to describe the nature of the accident, but also conducive to the recurrence of the accident process. It is found that the identification process is not only complicated, but also reduces the road capacity in a period of time. It is very valuable to identify the speed of road traffic accident video. In this paper, a new calibration method and the detection and tracking process of moving object (vehicle) are put forward by analyzing the calculation model and steps of camera calibration technology, moving target detection and tracking technology, and are realized by VC program. The automatic speed processing system based on VC is established. Finally, the effectiveness of the system is verified by an example. This paper studies the calibration method of surveillance camera, analyzes the calculation process, model and parameters of linear method and nonlinear method of camera calibration, and proposes a simple and stable calibration method based on the relationship between focus point and projection perspective. The precision is checked by specific environmental experiments. This paper studies the detection technology and tracking technology of moving target (vehicle). According to the difference of calculation model and calculation method, the optical flow method, inter-frame difference method and background subtraction method are analyzed, which are commonly used in moving target (vehicle) detection. After comparing the advantages and disadvantages of various technologies, a vehicle fluid region detection model combining background frame difference model and three-image frame difference model is designed. The extracted vehicle motion center is analyzed by micro-element inertial motion analysis. The vehicle fluid region tracking model is designed. The automatic processing system of speed calculation is developed. Based on VC platform, the module of video image reading and extracting is established, and the single frame image separation of video stream is completed. The mapping relation of coordinate points and the calculation module of spatial coordinate system are established, and the regional positioning module and tracking module of vehicle fluid are established, and the "vehicle speed calculation system" is developed, and the effectiveness of the system is verified by an example.
【學(xué)位授予單位】：長(zhǎng)安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：U491.31

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相關(guān)期刊論文 前5條

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2 蔡s

本文編號(hào)：1668246