本文選題：視頻摘要 + 目標(biāo)檢測(cè)��； 參考：《合肥工業(yè)大學(xué)》2016年碩士論文

【摘要】：隨著經(jīng)濟(jì)社會(huì)的快速發(fā)展,智能化的視頻監(jiān)控系統(tǒng)的快速普及,導(dǎo)致海量視頻數(shù)據(jù)爆炸式增長(zhǎng)。如何高效的處理、存儲(chǔ)視頻,提高視頻的利用率及瀏覽視頻的效率,一直是計(jì)算機(jī)視覺(jué)領(lǐng)域的研究熱門(mén)。為此,本文提出一種基于多目標(biāo)跟蹤的視頻摘要的方法。本文的主要研究工作及創(chuàng)新點(diǎn)如下：(1)本文提出基于廣義關(guān)聯(lián)聚類(lèi)圖的分層關(guān)聯(lián)多目標(biāo)跟蹤算法。把多目標(biāo)跟蹤看作圖的分割問(wèn)題,利用廣義關(guān)聯(lián)聚類(lèi)圖的算法,在給定一個(gè)滑動(dòng)時(shí)間窗口內(nèi),對(duì)某個(gè)目標(biāo)每幀出現(xiàn)的檢測(cè)圖片一次性數(shù)據(jù)融合,得到自適應(yīng)的軌跡片段。對(duì)軌跡片段進(jìn)一步數(shù)據(jù)融合,得到完整運(yùn)動(dòng)軌跡,完成多目標(biāo)跟蹤任務(wù)。本文的算法在復(fù)雜場(chǎng)景下,對(duì)遮擋處理,以及身份轉(zhuǎn)換問(wèn)題有很好的處理能力。公共數(shù)據(jù)集上的實(shí)驗(yàn)結(jié)果表明,本文的方法在多目標(biāo)跟蹤精度和跟蹤準(zhǔn)確度上都高于主流方法。(2)本文提出一種基于多目標(biāo)跟蹤的視頻摘要方法。將不同時(shí)刻出現(xiàn)的運(yùn)動(dòng)目標(biāo),在同一段視頻幀顯示,生成摘要視頻。本文的視頻摘要方法滿(mǎn)足項(xiàng)目對(duì)實(shí)時(shí)性的要求,以多目標(biāo)跟蹤的運(yùn)動(dòng)軌跡為基礎(chǔ),保留運(yùn)動(dòng)物體的空間信息的前提下,將運(yùn)動(dòng)目標(biāo)的檢測(cè)圖片重新組合整理,回貼到背景圖片中得到。通過(guò)本文方法得到的摘要視頻,能夠有效壓縮原始視頻,減少視頻的存儲(chǔ)空間,縮短視頻的瀏覽時(shí)間,提高視頻的利用率。(3)本文實(shí)現(xiàn)了視頻摘要系統(tǒng)軟件。本文使用C++編程語(yǔ)言,依靠第三方軟件庫(kù)OpenCV,編寫(xiě)出以MFC為界面的視頻摘要系統(tǒng)。系統(tǒng)界面簡(jiǎn)約清晰,操作容易,可以方便生成和瀏覽摘要視頻。
[Abstract]:With the rapid development of economy and society, the rapid popularization of intelligent video surveillance system leads to the explosive growth of massive video data.How to process and store video efficiently, improve the efficiency of video utilization and browse video has been a hot topic in the field of computer vision.Therefore, this paper presents a method of video summarization based on multi-target tracking.The main research work and innovation of this paper are as follows: 1) in this paper, a hierarchical association multi-target tracking algorithm based on generalized association clustering graph is proposed.The multi-target tracking is regarded as the segmentation problem of the graph, and the algorithm of generalized association clustering graph is used. In a given sliding time window, the detection pictures appear in each frame of a target are fused in a single time, and an adaptive trajectory segment is obtained.The track segment is further fused to obtain the complete motion trajectory, and the multi-target tracking task is completed.The algorithm in this paper can deal with occlusion and identity conversion in complex scenarios.Experimental results on common data sets show that the proposed method is superior to the mainstream method in tracking accuracy and accuracy. (2) this paper proposes a video summarization method based on multi-target tracking.The moving objects at different times are displayed in the same video frame, and the summary video is generated.The video summary method in this paper meets the real-time requirements of the project. Based on the motion track of multi-target tracking and keeping the spatial information of the moving object, the detection pictures of the moving object are recombined and arranged.Return to the background image to get it.The abstract video can compress the original video effectively, reduce the storage space of the video, shorten the browsing time of the video, and improve the utilization ratio of the video.This paper uses C programming language, relying on the third party software library OpenCV, to write a video summary system with MFC interface.System interface is simple and clear, easy to operate, can easily generate and browse summary video.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：TN948.6

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李斌;姚康澤;王巖;慈林林;萬(wàn)建偉;;基于灰關(guān)聯(lián)的分類(lèi)信息輔助多目標(biāo)跟蹤[J];信號(hào)處理;2009年03期

2 王汝夯;黃建國(guó);張群飛;;基于網(wǎng)絡(luò)層次分析的水下多目標(biāo)跟蹤排序方法[J];西北工業(yè)大學(xué)學(xué)報(bào);2009年05期

3 陳炳和;雷達(dá)多目標(biāo)跟蹤的數(shù)學(xué)表示[J];電子學(xué)報(bào);1988年02期

4 余少波,胡守仁,劉孟仁;雷達(dá)多目標(biāo)跟蹤的神經(jīng)網(wǎng)絡(luò)方法[J];電子學(xué)報(bào);1992年04期

5 王順奎;多目標(biāo)跟蹤用的多傳感器信息融合技術(shù)[J];紅外與激光技術(shù);1994年04期

6 E.W.Kamen ,劉勝厚;基于對(duì)稱(chēng)測(cè)量方程的多目標(biāo)跟蹤[J];艦船指揮控制系統(tǒng);1996年03期

7 劉維亭,張冰,朱志宇;多目標(biāo)跟蹤中的目標(biāo)位置及速度數(shù)據(jù)融合[J];船舶工程;2003年01期

8 路紅;費(fèi)樹(shù)岷;鄭建勇;張濤;;基于行為和部分觀測(cè)的多目標(biāo)跟蹤(英文)[J];Journal of Southeast University(English Edition);2008年04期

9 蔣戀華;甘朝暉;蔣e，

本文編號(hào)：1767534