本文選題：多攝像機(jī) + 無重疊視野域　； 參考：《北京交通大學(xué)》2014年碩士論文

【摘要】：隨著社會(huì)的發(fā)展,智能監(jiān)控技術(shù)逐步成為計(jì)算機(jī)視覺領(lǐng)域研究的重點(diǎn)。為了滿足監(jiān)控場(chǎng)景的需求,全面的獲得運(yùn)動(dòng)目標(biāo)信息,需要多個(gè)攝像機(jī)的協(xié)同合作。而對(duì)監(jiān)控范圍和計(jì)算量等因素的綜合考量,無重疊視野域的多攝像機(jī)目標(biāo)跟蹤技術(shù)受到了廣泛的關(guān)注。 在多攝像機(jī)無重疊視野域的監(jiān)控環(huán)境中,由于不同攝像機(jī)視野域內(nèi)的光照情況、目標(biāo)姿態(tài)等因素的不同,造成同一目標(biāo)在不同攝像機(jī)中的成像有所不同,進(jìn)而給多攝像機(jī)之間的目標(biāo)匹配帶來困難；同時(shí),由于多個(gè)攝像機(jī)之間存在盲區(qū),當(dāng)運(yùn)動(dòng)目標(biāo)消失在盲區(qū)時(shí),系統(tǒng)無法獲知目標(biāo)的運(yùn)動(dòng)信息,進(jìn)而無法實(shí)現(xiàn)對(duì)目標(biāo)的連續(xù)跟蹤。針對(duì)以上問題,本文對(duì)無重疊視野域多攝像機(jī)的目標(biāo)跟蹤技術(shù)進(jìn)行了研究,主要工作如下： 第一,實(shí)現(xiàn)了單攝像機(jī)下的目標(biāo)檢測(cè)與跟蹤,并對(duì)陰影去除和目標(biāo)跟蹤算法做了一定的改進(jìn)。 第二,針對(duì)多攝像機(jī)無重疊視野域的目標(biāo)跟蹤匹配問題,本文提出了兩種目標(biāo)匹配方法：(1)在有訓(xùn)練集的情況下,提出了一種基于亮度轉(zhuǎn)換函數(shù)子空間的分層目標(biāo)匹配法,利用概率主成分分析法對(duì)一對(duì)攝像機(jī)之間的亮度轉(zhuǎn)換函數(shù)空間進(jìn)行降維處理,并采取雙向映射,再結(jié)合目標(biāo)顏色分布的區(qū)域特征對(duì)目標(biāo)進(jìn)行匹配；(2)沒有訓(xùn)練集的情況下,在量化的HSV空間中,利用信息熵描述目標(biāo)顏色分布對(duì)目標(biāo)顏色特征的貢獻(xiàn)程度,在目標(biāo)顏色特征中融入顏色空間分布信息,從而提高了目標(biāo)匹配的準(zhǔn)確度。 第三,提出一種基于Agent的多攝像機(jī)無重疊視野域的目標(biāo)跟蹤方法。利用智能Agent代理攝像機(jī),從而使攝像機(jī)具有Agent的特性。多個(gè)攝像機(jī)之間可以通過消息通信進(jìn)行協(xié)同合作,進(jìn)而對(duì)監(jiān)控場(chǎng)景中出現(xiàn)的遮擋、盲區(qū)等現(xiàn)象給目標(biāo)跟蹤帶來的問題進(jìn)行處理。 第四,利用JADE平臺(tái)搭建多Agent系統(tǒng),初步實(shí)現(xiàn)多攝像機(jī)智能代理系統(tǒng)。并利用真實(shí)視頻數(shù)據(jù)驗(yàn)證基于Agent的多攝像機(jī)無重疊視野域的目標(biāo)跟蹤方法的有效性。
[Abstract]:With the development of society, intelligent monitoring technology has gradually become the focus of computer vision research.In order to meet the needs of the monitoring scene and obtain the moving target information comprehensively, the cooperation of multiple cameras is needed.However, considering the monitoring range and computational complexity, the multi-camera tracking technology without overlapping field of vision has been paid more and more attention.In the surveillance environment of multi-camera with no overlapping field of vision, the imaging of the same target in different cameras is different due to the different illumination and attitude of the target in different camera field.At the same time, because of the blind area between multiple cameras, the system can not get the moving information of the target when the moving object disappears in the blind area, and then can not realize the continuous tracking of the target.Aiming at the above problems, this paper studies the target tracking technology of multi-camera with no overlapping field of view. The main work is as follows:First, the target detection and tracking under single camera is realized, and the shadow removal and target tracking algorithms are improved.Secondly, aiming at the problem of target tracking and matching without overlapping field of view of multiple cameras, this paper proposes two target matching methods: 1) in the case of training set, a hierarchical target matching method based on brightness conversion function subspace is proposed.Using probabilistic principal component analysis (PPCA), the brightness conversion function space between a pair of cameras is reduced, and bidirectional mapping is adopted to match the target with the regional features of the color distribution.In the quantized HSV space, the information entropy is used to describe the contribution of the object color distribution to the target color feature, and the color space distribution information is incorporated into the target color feature, thus the accuracy of target matching is improved.Thirdly, a target tracking method based on Agent is proposed.The intelligent Agent proxy camera is used to make the camera have the characteristics of Agent.Multiple cameras can cooperate with each other through message communication to deal with the problems of target tracking caused by the occlusion and blind area in the monitoring scene.Fourthly, the multi-Agent system is built on JADE platform, and the multi-camera intelligent agent system is preliminarily realized.The real video data is used to verify the effectiveness of the target tracking method based on Agent.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP391.41;TN948.41

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本文編號(hào)：1749671