本文選題：視頻濃縮　切入點(diǎn)：多攝像頭　出處：《北京交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：面對(duì)廣泛應(yīng)用的網(wǎng)絡(luò)攝像頭和監(jiān)控?cái)z像頭,如何從海量的視頻快速地找到目標(biāo)成為了安防領(lǐng)域的重要問題。基于對(duì)象的視頻濃縮技術(shù)是目前處理這一問題的主要手段�；趯�(duì)象的視頻濃縮技術(shù)通過提取視頻中的活動(dòng)物體管道,在時(shí)間軸上移動(dòng)管道的位置,改變物體活動(dòng)的發(fā)生時(shí)間,生成一個(gè)濃縮摘要視頻,緊湊地展示物體活動(dòng)內(nèi)容,以達(dá)到縮短視頻時(shí)間長(zhǎng)度的目的�，F(xiàn)有的視頻濃縮技術(shù)大多是基于單攝像頭監(jiān)控場(chǎng)景,并取得了比較好的濃縮摘要結(jié)果。然而,隨著多攝像頭協(xié)同監(jiān)控場(chǎng)景的涌現(xiàn),現(xiàn)有技術(shù)不能取得令人滿意的結(jié)果。為此,本論文擬研究多攝像頭環(huán)繞環(huán)境下的視頻濃縮技術(shù)。本論文的主要研究?jī)?nèi)容及貢獻(xiàn)如下。1.提出一種環(huán)繞攝像頭環(huán)境下的視頻濃縮方法。不同于單攝像頭視頻濃縮方法,本方法利用多攝像頭在不同角度的拍攝畫面,使用概率生成地圖算法和基于K最短路徑優(yōu)化的多目標(biāo)跟蹤算法,有效地跟蹤物體在多攝像頭監(jiān)控區(qū)域內(nèi)的活動(dòng),從而提取出完整的物體活動(dòng)管道,進(jìn)而使用能量函數(shù)改變物體活動(dòng)管道的時(shí)間位置,獲得濃縮的摘要結(jié)果。實(shí)驗(yàn)結(jié)果表明,提出的算法可以有效濃縮多攝像頭監(jiān)控網(wǎng)絡(luò)中的視頻。2.設(shè)計(jì)并實(shí)現(xiàn)了環(huán)繞攝像頭環(huán)境下的視頻濃縮系統(tǒng)。在進(jìn)行摘要結(jié)果的可視化展示時(shí),將物體以三維矩形面的形式展現(xiàn)在模擬的三維偽場(chǎng)景空間中,物體的位移活動(dòng)通過移動(dòng)三維矩形面在模擬地平面上的位置來體現(xiàn),而物體的身體活動(dòng)則通過在矩形面上渲染原視頻中相應(yīng)時(shí)刻的物體活動(dòng)圖像來表現(xiàn)。因此,系統(tǒng)用戶可以改變觀察的視點(diǎn)位置和視角方向,以減少觀察視線上的物體重疊遮擋現(xiàn)象,獲得更好的用戶體驗(yàn)。
[Abstract]:In the face of widely used webcams and surveillance cameras, How to quickly find the target from mass video has become an important problem in the field of security. Object-based video enrichment is the main method to deal with this problem. Moving object pipes in frequency, Move the tube on the timeline, change the time when the object occurs, and generate a condensed summary video showing the object's content in a compact way. In order to shorten the length of video time, most of the existing video enrichment techniques are based on single camera surveillance scene, and get a good condensed summary result. However, with the emergence of multi-camera cooperative surveillance scene, The existing technology is not able to achieve satisfactory results. To this end, The main contents and contributions of this thesis are as follows. 1. A video concentration method under the surrounding camera environment is proposed, which is different from the single camera video concentration method. The method uses multi-camera to shoot pictures at different angles, uses probability map generation algorithm and multi-target tracking algorithm based on K shortest path optimization, effectively tracks the activity of objects in multi-camera monitoring area. In order to extract the whole moving pipe, the energy function is used to change the time position of the moving pipe, and the condensed summary results are obtained. The experimental results show that, The proposed algorithm can effectively concentrate the video in the multi-camera monitoring network. A video concentration system is designed and implemented in the surrounding camera environment. The object is displayed as a three-dimensional rectangular plane in the simulated three-dimensional pseudo-scene space, and the displacement activity of the object is reflected by moving the three-dimensional rectangular plane in the simulated ground plane. The body activity of the object is represented by rendering the image of the object moving at the corresponding time in the original video on the rectangular surface. Therefore, the user of the system can change the view position and angle of view. In order to reduce the sight of the object overlap occlusion phenomenon, to obtain a better user experience.
【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】：2017
【分類號(hào)】：TP391.41

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本文編號(hào)：1618914