基于多核DSP的運動目標跟蹤算法的研究與實現(xiàn)
[Abstract]:With the development of society, video surveillance system has entered into thousands of households, intelligent monitoring system is the main trend of development, and in the monitoring system to achieve the tracking of moving targets is an important embodiment of intelligent. In this paper, intelligent video surveillance is taken as the research focus. Firstly, the realization platform of target tracking algorithm is designed, which is based on multi-core DSP video surveillance system, and then the moving target tracking algorithm is studied. Finally, the algorithm is implemented on the multi-core DSP monitoring platform. The research focus of this paper is as follows: (1) this paper designs a special video monitoring system based on TMS320DM8168 (DM8168) multi-core processor, which realizes the functions of video acquisition, processing, display and network output. The characteristic of the system is that the video stream frame is designed according to the actual demand, the video is transformed by TILER, OSD logo is added, mosaic and so on. In order to realize the network output function of the video, the streaming media server program is designed. In the design, the stability of the system is improved by adding AVS function, and the expansibility of the system is enhanced by designing PCIe driver. (2) in this paper, feature extraction algorithm is an important part of target tracking algorithm. In this paper, by comparing various feature extraction algorithms, we select the SURF algorithm, which takes both performance and efficiency into account, to extract the feature of the target, and use a combination of multiple matching algorithms to match the SURF feature of the target. The reasonable simulation flow is designed in the whole test of the target tracking algorithm. Some common problems, such as the change of the target shape, the occlusion of the target, the influence of the shadow of the target, and so on, are proposed. The simulation results are analyzed. (3) according to the characteristics of DM8168 multi-core monitoring platform, the realization flow of target tracking algorithm with multiple cores is designed, and the algorithm is implemented according to the flow chart. Because of the high requirement of real-time performance, the algorithm is optimized deeply according to the characteristics of DSP, and the speed of the algorithm is improved. The result is verified by testing the target tracking algorithm. (4) in order to better guarantee the performance and speed of the algorithm, the SURF algorithm, which takes the longest time in the target tracking algorithm, is implemented on the platform of TMS320C6678 (C6678). In the implementation, the whole task is partitioned by the way of dividing pictures, so that each kernel processes one sub-task. Through the analysis of the processing results, the correctness of the method is proved, and the speed of the algorithm is greatly improved. By exploring the implementation of SURF algorithm on C6678 platform, this paper lays a foundation for the realization of the following target tracking algorithm on the whole platform of DM8168 C6678.
【學位授予單位】:電子科技大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TP391.41;TN948.6
【參考文獻】
相關期刊論文 前7條
1 黃凱奇;陳曉棠;康運鋒;譚鐵牛;;智能視頻監(jiān)控技術綜述[J];計算機學報;2015年06期
2 仇大偉;劉靜;;復雜場景下基于特征點匹配的目標跟蹤算法[J];山東科學;2014年04期
3 倪郁東;王晨;;基于窗口的Surf目標跟蹤[J];安徽大學學報(自然科學版);2014年04期
4 張坤;許廷發(fā);王平;馮亮;;高精度實時全幀頻SURF電子穩(wěn)像方法[J];光學精密工程;2011年08期
5 陳書明;萬江華;魯建壯;劉仲;孫海燕;孫永節(jié);劉衡竹;劉祥遠;李振濤;徐毅;陳小文;;YHFT-QDSP:High-Performance Heterogeneous Multi-Core DSP[J];Journal of Computer Science & Technology;2010年02期
6 信師國;劉慶磊;劉全賓;;網絡視頻監(jiān)控系統(tǒng)現(xiàn)狀和發(fā)展趨勢[J];信息技術與信息化;2010年01期
7 王亞琴;董彥榮;薄靜儀;;流媒體傳輸協(xié)議及應用[J];辦公自動化;2009年24期
相關博士學位論文 前6條
1 謝凌曦;基于局部特征的圖像表示模型理論與實踐[D];清華大學;2015年
2 侯躍恩;基于稀疏表示的視覺目標跟蹤算法研究[D];華南理工大學;2014年
3 劉晴;基于區(qū)域特征的目標跟蹤算法研究[D];北京理工大學;2014年
4 牛長鋒;復雜背景下視頻運動目標跟蹤的研究[D];北京理工大學;2010年
5 郭龍源;計算機視覺立體匹配相關理論與算法研究[D];南京理工大學;2009年
6 夏永泉;計算機視覺中雙目匹配相關技術研究[D];南京理工大學;2007年
相關碩士學位論文 前6條
1 王禹程;基于局部特征的運動目標跟蹤算法的研究與實現(xiàn)[D];電子科技大學;2016年
2 王朋;基于DM8168的網絡智能監(jiān)控系統(tǒng)的研究與實現(xiàn)[D];電子科技大學;2015年
3 陳誠;基于雙目視覺的運動目標跟蹤算法研究與應用[D];哈爾濱工業(yè)大學;2014年
4 鄒依峰;智能視頻監(jiān)控中的行人檢測與跟蹤方法研究[D];中國科學技術大學;2011年
5 卜珂;基于SURF的圖像配準與拼接技術研究[D];大連理工大學;2009年
6 王典;基于混合高斯的背景建模與陰影抑制算法研究[D];西北工業(yè)大學;2006年
,本文編號:2401763
本文鏈接:http://sikaile.net/kejilunwen/xinxigongchenglunwen/2401763.html