【摘要】：一直以來,智能監(jiān)控技術(shù)都是計(jì)算機(jī)視覺領(lǐng)域的研究熱點(diǎn)。隨著人們對生活品質(zhì)要求的不斷提高,傳統(tǒng)的監(jiān)控系統(tǒng)早已不能滿足人們的應(yīng)用需求。針對傳統(tǒng)監(jiān)控系統(tǒng)監(jiān)控目標(biāo)的清晰度有限和冗余數(shù)據(jù)量大的問題,本文提出一種多攝像機(jī)的雙視場運(yùn)動目標(biāo)智能監(jiān)控系統(tǒng),其中寬視場主攝像機(jī)負(fù)責(zé)對大范圍視野進(jìn)行整體監(jiān)控,并調(diào)度窄視場從攝像機(jī)對指定的運(yùn)動目標(biāo)進(jìn)行主動跟蹤,窄視場從攝像機(jī)負(fù)責(zé)獲取高分辨率的目標(biāo)圖像。本文的主要工作及創(chuàng)新點(diǎn)概括如下:(1)不同于傳統(tǒng)的多攝像機(jī)系統(tǒng),本文對監(jiān)控系統(tǒng)的攝像機(jī)進(jìn)行了分工,以高分辨率的運(yùn)動目標(biāo)圖像代替視頻序列,在控制產(chǎn)生的冗余數(shù)據(jù)量的前提下,既實(shí)現(xiàn)了大范圍的整體監(jiān)控又得到了運(yùn)動目標(biāo)的細(xì)節(jié)信息。(2)對圖像畸變校正算法、運(yùn)動目標(biāo)檢測算法、運(yùn)動目標(biāo)跟蹤算法和目標(biāo)交接算法分別進(jìn)行了研究和實(shí)現(xiàn)。重點(diǎn)研究了攝像機(jī)標(biāo)定技術(shù)、背景差分法的不同背景模型、顏色特征匹配、不同顏色空間的特點(diǎn)、基于SURF(Speeded Up Robust features)算法和基于 ORB(Oriented FAST and Rotated BRIEF)算法的角點(diǎn)匹配技術(shù)。(3)結(jié)合信息熵的概念,對運(yùn)動目標(biāo)檢測的背景差分法進(jìn)行改進(jìn),改進(jìn)的算法兼顧了計(jì)算速度和檢測精度。(4)針對本文的應(yīng)用,提出融合角點(diǎn)特征和顏色特征的運(yùn)動目標(biāo)交接算法,實(shí)現(xiàn)了雙視場運(yùn)動目標(biāo)的實(shí)時準(zhǔn)確交接。(5)在 VS2010(Microsoft Visual Studio2010)平臺上使用 C++語言實(shí)現(xiàn)了系統(tǒng)的視頻采集模塊、圖像校正模塊、運(yùn)動目標(biāo)檢測模塊、目標(biāo)交接模塊、PTZ(Pan-Tilt-Zoom)攝像機(jī)云臺控制模塊和運(yùn)動目標(biāo)主動跟蹤模塊。
[Abstract]:Intelligent monitoring technology has always been a hot topic in the field of computer vision. With the improvement of the quality of life, the traditional monitoring system can not meet the needs of people. In order to solve the problems of limited clarity and large redundant data amount in traditional monitoring system, this paper presents an intelligent monitoring system for moving targets with two fields of view with multiple cameras. The wide field of view main camera is responsible for the overall monitoring of the wide field of view, and the narrow field of view is responsible for actively tracking the designated moving target from the camera, and the narrow field of view is responsible for obtaining the high resolution target image from the camera. The main work and innovations of this paper are summarized as follows: (1) different from the traditional multi-camera system, this paper divides the cameras of the surveillance system and replaces the video sequences with high-resolution moving target images. On the premise of controlling the amount of redundant data generated by the control system, both the global monitoring and the detailed information of the moving object are realized. (2) the image distortion correction algorithm, the moving target detection algorithm, the image distortion correction algorithm, the moving target detection algorithm, the image distortion correction algorithm, the moving target detection algorithm, The moving target tracking algorithm and the target handover algorithm are studied and implemented respectively. The techniques of camera calibration, background difference method, color feature matching, and different color space are studied in detail. Corner matching technology based on SURF (Speeded Up Robust features) algorithm and ORB (Oriented FAST and Rotated BRIEF) algorithm. (3) based on the concept of information entropy, the background difference method for moving target detection is improved. The improved algorithm takes into account the computation speed and the detection accuracy. (4) aiming at the application of this paper, a new algorithm of moving target handover is proposed, which combines corner feature and color feature. It realizes the real-time and accurate transfer of the moving object in the double field of view. (5) the video acquisition module, the image correction module, the moving target detection module and the target handover module are realized by using C language on the VS2010 (Microsoft Visual Studio2010 platform. PTZ (Pan-Tilt-Zoom) camera control module and moving target active tracking module.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

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本文編號：2388850