本文選題：智能視頻監(jiān)控 + 嵌入式智能相機　； 參考：《上海交通大學》2012年碩士論文

【摘要】：隨著安防系統(tǒng)在公共治安和預防恐怖襲擊等方面的大量應用,人們對大規(guī)模智能視頻監(jiān)控系統(tǒng)的需求日益增長。目前基于集中處理的智能視頻監(jiān)控系統(tǒng)由于成本、處理能力、存儲能力等因素的限制,無法大規(guī)模的使用。嵌入式智能相機具有低成本、低功耗、易擴展的特點,因此嵌入式智能相機網(wǎng)絡成為未來大規(guī)模監(jiān)控系統(tǒng)的主要發(fā)展方向。本文重點研究基于ARM的嵌入式智能相機的系統(tǒng)搭建、檢測算法和覆蓋問題,主要工作有如下三個方面。 一、嵌入式智能相機平臺搭建。在分析嵌入式智能相機特點的基礎上,提出新型的高性能嵌入式智能相機設計方案。該方案采用基于ARM9處理器的PXA270開發(fā)板作為硬件系統(tǒng),并開發(fā)了多個滿足視頻監(jiān)控基本任務的軟件模塊。 二、基于嵌入式智能相機的目標檢測算法設計。針對嵌入式智能相機有限的計算和存儲能力,提出基于輪廓判定與分類的輕量級目標檢測方法。該方法采用“加性增、乘性減”(AIMD)的方法進行輪廓檢測,然后對檢測到的運動區(qū)域進行分類,從而實現(xiàn)前景的辨認和背景的更新。實驗證明,所提方法具有速度快、魯棒性強的特點。 三、多相機的優(yōu)化覆蓋策略。由于單個相機的視野限制,監(jiān)控場景往往要求被多個相機共同覆蓋。為了降低監(jiān)控覆蓋成本,結合監(jiān)控目標的異構需求,提出基于概率的相機優(yōu)化覆蓋策略。該方法充分利用智能相機所具有的PTZ性能,計算各個位置的覆蓋概率,在滿足各個監(jiān)控位置的不同監(jiān)控需求的基礎上,有效地降低了多相機條件下的監(jiān)控成本。最后通過仿真驗證了所提方法的有效性。
[Abstract]:With the extensive application of security system in public security and preventing terrorist attacks, the demand for large-scale intelligent video surveillance system is increasing day by day. At present, intelligent video surveillance system based on centralized processing can not be used on a large scale because of the limitation of cost, processing capacity, storage capacity and so on. The embedded intelligent camera has the characteristics of low cost, low power consumption and easy to expand, so the embedded intelligent camera network will become the main development direction of the large-scale monitoring system in the future. This paper focuses on the system construction, detection algorithm and coverage of embedded intelligent camera based on ARM. The main work is as follows. First, the embedded intelligent camera platform is built. Based on the analysis of the characteristics of embedded intelligent camera, a new design scheme of high performance embedded intelligent camera is proposed. The PXA270 development board based on ARM9 processor is used as the hardware system, and several software modules to meet the basic tasks of video surveillance are developed. Second, the design of target detection algorithm based on embedded intelligent camera. Aiming at the limited computing and storage ability of embedded intelligent camera, a lightweight target detection method based on contour determination and classification is proposed. In this method, "additive increase, multiplicative subtraction" (AIMD) is used for contour detection, and then the detected motion regions are classified to realize foreground recognition and background updating. Experimental results show that the proposed method is fast and robust. Third, the optimal coverage strategy for multiple cameras. As a result of the single camera's visual field limit, the monitoring scene often needs to be covered by multiple cameras. In order to reduce the cost of monitoring coverage, a probabilistic camera coverage optimization strategy is proposed to meet the heterogeneous requirements of monitoring targets. This method makes full use of the PTZ performance of the intelligent camera, calculates the coverage probability of each location, and effectively reduces the monitoring cost under the condition of multiple cameras on the basis of satisfying the different monitoring requirements of each monitoring position. Finally, the effectiveness of the proposed method is verified by simulation.
【學位授予單位】：上海交通大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TP277;TP368.1

【引證文獻】

相關碩士學位論文 前1條

1 肖龍;攝像頭傳感器網(wǎng)絡目標跟蹤、識別及覆蓋定位技術研究[D];上海交通大學;2013年

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本文編號：1940143