發(fā)布時(shí)間：2018-06-22 14:55

  本文選題：視頻增強(qiáng)虛擬環(huán)境 + PTZ相機(jī)　； 參考：《南京師范大學(xué)》2016年碩士論文

【摘要】：PTZ(Pan-Tilt-Zoom)相機(jī)在安防中廣泛應(yīng)用,用于安防領(lǐng)域的視頻監(jiān)控系統(tǒng)一般通過多路獨(dú)立的視頻監(jiān)視器觀看,由于視頻間是分散、相互獨(dú)立的,監(jiān)控人員往往因?yàn)樾畔⒉煌暾B貫而產(chǎn)生疏漏。視頻增強(qiáng)虛擬環(huán)境技術(shù)(AVE)通過把二維視頻嵌入三維虛擬場(chǎng)景,實(shí)現(xiàn)了虛景與實(shí)景相融合,抽象與現(xiàn)實(shí)相結(jié)合,有利于從宏觀上把握視頻與場(chǎng)景的空間關(guān)聯(lián),為地理場(chǎng)景的認(rèn)知提供更為全面的時(shí)空信息,更為宏觀的觀察視角,更好地服務(wù)安防等領(lǐng)域。視頻圖像與虛擬三維場(chǎng)景融合的前提是相機(jī)在虛擬場(chǎng)景中的注冊(cè)。通過引入人工標(biāo)志物是相機(jī)注冊(cè)的常用方法,但這種方法難以應(yīng)用于相機(jī)動(dòng)態(tài)調(diào)整的場(chǎng)景。大多數(shù)監(jiān)控相機(jī)都是可以動(dòng)態(tài)調(diào)整姿態(tài)與焦距.的PTZ相機(jī),除非廠商軟件支持,無法實(shí)時(shí)獲取相機(jī)調(diào)整后的姿態(tài)和焦距等信息,從而造成視頻與場(chǎng)景無法準(zhǔn)確融合。本文基于計(jì)算機(jī)視覺的理論和技術(shù),對(duì)PTZ相機(jī)視頻與虛擬三維場(chǎng)景的融合方法進(jìn)行了相關(guān)研究,主要研究?jī)?nèi)容與成果如下:(1)分析了相機(jī)的成像模型與虛擬場(chǎng)景中虛擬相機(jī)的成像模型的關(guān)系,并明確了相機(jī)內(nèi)外參數(shù)與三維渲染引擎中虛擬相機(jī)設(shè)置參數(shù)的關(guān)系,在無需引入額外的人工標(biāo)志物的情況下,通過反投影方法獲得3D模型世界坐標(biāo),然后利用線性方法快速估計(jì)和非線性方法迭代優(yōu)化求值相結(jié)合的方法,對(duì)視頻相機(jī)的初始參數(shù)進(jìn)行計(jì)算,實(shí)現(xiàn)相機(jī)在虛擬場(chǎng)景中的初始注冊(cè)。(2)對(duì)PTZ相機(jī)參數(shù)的實(shí)時(shí)變化進(jìn)行了分析,提出了基于計(jì)算機(jī)視覺理論的PTZ相機(jī)實(shí)時(shí)跟蹤與注冊(cè)方法。該方法首先通過視頻幀全局特征快速檢測(cè)出相機(jī)參數(shù)是否發(fā)生變化,然后再使用局部特征精確匹配對(duì)相機(jī)進(jìn)行實(shí)時(shí)注冊(cè),確保PTZ相機(jī)調(diào)整后視頻與虛擬場(chǎng)景的自動(dòng)準(zhǔn)確融合。上述方法既兼顧了融合效率與融合質(zhì)量,也避免了人工調(diào)整的繁瑣性和滯后性。(3)在視頻相機(jī)已經(jīng)注冊(cè)的前提下,本文分析了虛擬相機(jī)投影視頻紋理的原理,并結(jié)合ShadowMap陰影算法和GPU Shader技術(shù),基于OpensSceneGraph三維渲染引擎實(shí)現(xiàn)了 PTZ相機(jī)視頻與虛擬三維場(chǎng)景的實(shí)時(shí)融合。實(shí)驗(yàn)結(jié)果驗(yàn)證了本文方法的有效性和可靠性。本文在PTZ相機(jī)實(shí)時(shí)注冊(cè)方面所做的相關(guān)研究也可以推廣到移動(dòng)相機(jī)視頻的實(shí)時(shí)注冊(cè),有助于拓展視頻增強(qiáng)虛擬環(huán)境的應(yīng)用領(lǐng)域。
[Abstract]:PTZ (Pan-Tilt-Zoom) camera is widely used in security. The video surveillance system used in security field is generally viewed by multiple independent video monitors. Surveillance personnel often because the information is not complete and coherent and produce omissions. Video Enhancement Virtual Environment (AVE) integrates virtual scene and real scene by embedding 2D video into 3D virtual scene, which is helpful to grasp the spatial association between video and scene from macro view. It provides more comprehensive temporal and spatial information for the cognition of geographical scene, a more macroscopic perspective of observation, and better service for the field of security and defense. The premise of fusion of video image and virtual 3D scene is the registration of camera in virtual scene. The introduction of artificial markers is a common method for camera registration, but it is difficult to apply to the scene of camera dynamic adjustment. Most surveillance cameras are able to dynamically adjust the attitude and focal length. The PTZ camera, unless supported by the vendor software, can not obtain the camera's adjusted posture and focal length in real time, resulting in the video and scene can not be accurately integrated. Based on the theory and technology of computer vision, this paper studies the fusion method of PTZ camera video and virtual 3D scene. The main contents and results are as follows: (1) the relationship between camera imaging model and virtual camera imaging model in virtual scene is analyzed, and the relationship between camera internal and external parameters and virtual camera setting parameters in 3D rendering engine is clarified. Without introducing additional artificial markers, the 3D model world coordinates are obtained by backprojection method, and then the linear method is used to estimate the world coordinates quickly and the nonlinear method is used to iteratively optimize the evaluation. The initial parameters of the video camera are calculated to realize the initial registration of the camera in the virtual scene. (2) the real-time change of the parameters of the PTZ camera is analyzed and a method of real-time tracking and registration of the PTZ camera based on the theory of computer vision is proposed. In this method, the camera parameters are quickly detected by the global feature of the video frame, and then the real time registration of the camera is carried out by using the local feature accurate matching to ensure the automatic and accurate fusion between the video and the virtual scene after the PTZ camera is adjusted. This method not only takes into account the fusion efficiency and fusion quality, but also avoids the complexity and lag of manual adjustment. (3) on the premise that the video camera is registered, this paper analyzes the principle of projecting video texture of virtual camera. Combined with ShadowMap shadow algorithm and GPU Shader technology, the real-time fusion of PTZ camera video and virtual 3D scene is realized based on OpensSceneGraph 3D rendering engine. The experimental results show that the proposed method is effective and reliable. In this paper, the research on the real-time registration of PTZ camera can also be extended to the real-time registration of mobile camera video, which is helpful to expand the application field of video enhancement virtual environment.
【學(xué)位授予單位】：南京師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41;TP391.9

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 崔智高;李艾華;王濤;徐斌;蔡艷平;;一種基于參數(shù)重估計(jì)和分層匹配的PTZ相機(jī)參數(shù)修正算法[J];光電子·激光;2015年10期

2 周忠;周頤;肖江劍;;虛擬現(xiàn)實(shí)增強(qiáng)技術(shù)綜述[J];中國(guó)科學(xué):信息科學(xué);2015年02期

3 簡(jiǎn)洪登;范湘濤;;基于GLSL的多重視頻紋理映射與融合[J];計(jì)算機(jī)工程與設(shè)計(jì);2014年11期

4 高宏偉;王慧科;劉傳銀;李斌;;單相機(jī)變焦圖像深度估計(jì)技術(shù)研究[J];計(jì)算機(jī)科學(xué);2014年S1期

5 張雪波;路晗;方勇純;李寶全;;室外環(huán)境下PTZ攝像機(jī)全自動(dòng)標(biāo)定技術(shù)及其應(yīng)用[J];機(jī)器人;2013年04期

6 馬原野;趙剛;何彬;;3DGIS與多視頻融合系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)[J];計(jì)算機(jī)應(yīng)用與軟件;2012年06期

7 王文斌;劉桂華;劉先勇;邱志強(qiáng);;本質(zhì)矩陣五點(diǎn)算法偽解的兩種剔除策略[J];光電工程;2010年08期

8 楊華芬;鄭歡鳴;;基于內(nèi)容的視頻關(guān)鍵幀提取技術(shù)研究[J];福建電腦;2010年05期

9 孟曉橋,胡占義;攝像機(jī)自標(biāo)定方法的研究與進(jìn)展[J];自動(dòng)化學(xué)報(bào);2003年01期

相關(guān)博士學(xué)位論文 前4條

1 王延可;增強(qiáng)現(xiàn)實(shí)幾何一致性相關(guān)問題研究[D];山東大學(xué);2014年

2 周凡;視頻影像增強(qiáng)虛擬三維場(chǎng)景的注冊(cè)與渲染方法研究[D];武漢大學(xué);2014年

3 夏軍營(yíng);空間目標(biāo)的單目視覺位姿測(cè)量方法研究[D];國(guó)防科學(xué)技術(shù)大學(xué);2012年

4 史艷瓊;變焦攝像機(jī)跟蹤定位與測(cè)量技術(shù)[D];合肥工業(yè)大學(xué);2012年

相關(guān)碩士學(xué)位論文 前3條

1 扎西次仁;復(fù)雜場(chǎng)景中實(shí)時(shí)全局光照模型研究[D];北京郵電大學(xué);2015年

2 徐鑫;紅外圖像拼接技術(shù)研究[D];東華大學(xué);2014年

3 吳華;基于普通攝像機(jī)的雙目立體視覺三維重構(gòu)技術(shù)研究[D];廣西大學(xué);2012年

，

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