天堂国产午夜亚洲专区-少妇人妻综合久久蜜臀-国产成人户外露出视频在线-国产91传媒一区二区三区

智能視頻監(jiān)控中的運(yùn)動(dòng)目標(biāo)檢測(cè)相關(guān)技術(shù)研究

發(fā)布時(shí)間:2018-08-24 11:32
【摘要】:智能視頻監(jiān)控技術(shù)的研究屬于近些年來(lái)在計(jì)算機(jī)視覺(jué)領(lǐng)域新興的方向。它主要的研究目標(biāo)是通過(guò)計(jì)算機(jī)視覺(jué)技術(shù)、圖像視頻處理技術(shù)和人工智能技術(shù),對(duì)監(jiān)控視頻的內(nèi)容進(jìn)行描述、分析和理解,同時(shí)根據(jù)分析處理所得的結(jié)果對(duì)監(jiān)控系統(tǒng)進(jìn)行控制,進(jìn)而使得視頻監(jiān)控系統(tǒng)能夠滿足人們對(duì)于智能化的要求水平。它的主要研究?jī)?nèi)容包括:監(jiān)控視頻中運(yùn)動(dòng)物體的檢測(cè)、跟蹤、識(shí)別和行為分析等。本文主要的研究?jī)?nèi)容為智能視頻監(jiān)控中的運(yùn)動(dòng)目標(biāo)檢測(cè)提取方法。針對(duì)傳統(tǒng)的運(yùn)動(dòng)目標(biāo)檢測(cè)諸多方法中經(jīng)常出現(xiàn)的易受光照變化、復(fù)雜背景、陰影等因素影響的問(wèn)題,提出了一種由混合高斯模型、邊緣檢測(cè)法與連續(xù)幀間差分法三種算法相結(jié)合的運(yùn)動(dòng)目標(biāo)檢測(cè)算法。該算法通過(guò)混合高斯模型在時(shí)間域上進(jìn)行背景的建模與更新,在空間域上利用由邊緣檢測(cè)算法、連續(xù)幀間差分法以及混合高斯模型相結(jié)合的檢測(cè)算法得出初始的運(yùn)動(dòng)目標(biāo)輪廓,并且經(jīng)過(guò)后續(xù)的運(yùn)算處理,得到完善的所需運(yùn)動(dòng)物體。該算法不僅能夠很好的適應(yīng)所處場(chǎng)景中的背景干擾與漸變的光照條件,而且能夠克服傳統(tǒng)算法中對(duì)于目標(biāo)檢測(cè)不準(zhǔn)確、邊緣檢測(cè)不完整、容易產(chǎn)生空洞和重影等問(wèn)題的發(fā)生。實(shí)驗(yàn)結(jié)果顯示該運(yùn)算方法復(fù)雜度相對(duì)適中,具有比較好的實(shí)時(shí)性和魯棒性,對(duì)運(yùn)動(dòng)物體檢測(cè)的精確度較高。運(yùn)動(dòng)目標(biāo)檢測(cè)是智能視頻監(jiān)控中的一個(gè)重要環(huán)節(jié),而運(yùn)動(dòng)目標(biāo)的陰影檢測(cè)又是運(yùn)動(dòng)物體檢測(cè)的一個(gè)重要步驟。對(duì)于目標(biāo)陰影檢測(cè)的正確與否將直接影響到對(duì)目標(biāo)物體的檢測(cè)結(jié)果。通過(guò)對(duì)各種陰影檢測(cè)方法的學(xué)習(xí)與研究,我們發(fā)現(xiàn)僅僅通過(guò)一種特征進(jìn)行處理并不能準(zhǔn)確的檢測(cè)出陰影。因此,本文提出了一種混合顏色信息、光學(xué)不變性以及紋理特征的目標(biāo)陰影檢測(cè)方法,通過(guò)綜合分析三種信息檢測(cè)的結(jié)果,從而實(shí)現(xiàn)對(duì)陰影的有效確定。該算法能夠有效地結(jié)合各種方法的優(yōu)勢(shì),在實(shí)驗(yàn)中取得了較好的效果和運(yùn)行效率。
[Abstract]:The research of intelligent video surveillance technology is a new direction in the field of computer vision in recent years. Its main research goal is to describe, analyze and understand the content of surveillance video through computer vision technology, image and video processing technology and artificial intelligence technology, and control the monitoring system according to the result of analysis and processing. So that the video surveillance system can meet the requirements of people for the level of intelligence. Its main research contents include: detection, tracking, recognition and behavior analysis of moving objects in surveillance video. The main research content of this paper is the method of moving target detection in intelligent video surveillance. A mixed Gao Si model is proposed to solve the problems which are often affected by the changes of illumination, complex background, shadow and so on in the traditional methods of moving target detection. A moving target detection algorithm based on edge detection and continuous frame difference. The algorithm uses the hybrid Gao Si model to model and update the background in the time domain, and uses the edge detection algorithm, the continuous inter-frame difference method and the mixed Gao Si model to obtain the initial moving target contour in the spatial domain, which is composed of the edge detection algorithm, the continuous inter-frame difference method and the mixed Gao Si model. And after the subsequent processing, we can get the perfect moving object. This algorithm can not only adapt to the background interference and the gradual illumination condition in the scene, but also overcome the problems of inaccurate target detection and incomplete edge detection in traditional algorithms. The experimental results show that the algorithm is relatively moderate in complexity, real-time and robust, and has high accuracy for moving object detection. Moving target detection is an important part of intelligent video surveillance, and shadow detection of moving object is an important step in moving object detection. Whether the target shadow detection is correct or not will directly affect the target object detection results. Through the study of various shadow detection methods, we find that only one feature processing can not accurately detect shadow. Therefore, in this paper, a method of shadow detection based on mixed color information, optical invariance and texture features is proposed. By synthetically analyzing the results of three kinds of information detection, the shadow can be effectively determined. The algorithm can effectively combine the advantages of various methods and achieve good results and operational efficiency in the experiment.
【學(xué)位授予單位】:天津理工大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:TP391.41;TN948.6

【參考文獻(xiàn)】

相關(guān)期刊論文 前6條

1 柏柯嘉;劉偉銘;湯義;;基于Gabor小波和顏色模型的陰影檢測(cè)算法[J];華南理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2009年01期

2 黃士科,陶琳,張?zhí)煨?一種改進(jìn)的基于光流的運(yùn)動(dòng)目標(biāo)檢測(cè)方法[J];華中科技大學(xué)學(xué)報(bào)(自然科學(xué)版);2005年05期

3 張磊;項(xiàng)學(xué)智;趙春暉;;基于光流場(chǎng)與水平集的運(yùn)動(dòng)目標(biāo)檢測(cè)[J];計(jì)算機(jī)應(yīng)用;2009年04期

4 王陳陽(yáng);周明全;耿國(guó)華;;基于自適應(yīng)背景模型運(yùn)動(dòng)目標(biāo)檢測(cè)[J];計(jì)算機(jī)技術(shù)與發(fā)展;2007年04期

5 張玉榮;涂錚錚;羅斌;;基于幀差和小波包分析算法的運(yùn)動(dòng)目標(biāo)檢測(cè)[J];計(jì)算機(jī)技術(shù)與發(fā)展;2008年01期

6 李子青;;國(guó)內(nèi)智能視頻監(jiān)控技術(shù)的發(fā)展[J];智能建筑;2008年01期

相關(guān)博士學(xué)位論文 前1條

1 徐治非;視頻監(jiān)控中運(yùn)動(dòng)目標(biāo)檢測(cè)與跟蹤方法研究[D];上海交通大學(xué);2009年

相關(guān)碩士學(xué)位論文 前1條

1 趙俊;智能視頻監(jiān)控系統(tǒng)關(guān)鍵技術(shù)研究[D];西安電子科技大學(xué);2007年

,

本文編號(hào):2200692

資料下載
論文發(fā)表

本文鏈接:http://sikaile.net/kejilunwen/wltx/2200692.html


Copyright(c)文論論文網(wǎng)All Rights Reserved | 網(wǎng)站地圖 |

版權(quán)申明:資料由用戶7fcfb***提供,本站僅收錄摘要或目錄,作者需要?jiǎng)h除請(qǐng)E-mail郵箱bigeng88@qq.com