本文選題：視頻 + 嵌入式中間件　； 參考：《上海海洋大學(xué)》2017年碩士論文

【摘要】：I視頻作為現(xiàn)代數(shù)據(jù)的重要來源,其相關(guān)技術(shù)的重要性日顯突出。盡管目前視頻技術(shù)在農(nóng)業(yè)、工業(yè)、軍事、安全、交通等領(lǐng)域已經(jīng)有較為普遍的應(yīng)用,但物聯(lián)網(wǎng)視頻技術(shù)仍有諸多問題亟須解決,如訪問接口不統(tǒng)一、前端計(jì)算處理能力弱、不能向用戶有針對(duì)性地提供數(shù)據(jù),多數(shù)引用環(huán)境中,視頻流要經(jīng)由感知層、傳輸層到處理層再至應(yīng)用層,通常伴有著一定的延遲,影響物聯(lián)網(wǎng)視頻監(jiān)控的實(shí)時(shí)性與處理效率。為方便視頻的轉(zhuǎn)發(fā),減少視頻、圖像數(shù)據(jù)處理延遲,提高物聯(lián)網(wǎng)數(shù)據(jù)傳輸與處理效率,本文基于RTSP(Real Time Streaming Protocol)協(xié)議及“就地”處理(Process in Field)思想提出了一種嵌入式視頻中間件技術(shù),通過低功耗、低成本、高性能的嵌入式異構(gòu)多核計(jì)算系統(tǒng)對(duì)現(xiàn)場(chǎng)視頻進(jìn)行采集、處理與轉(zhuǎn)發(fā),本文所做的主要工作包括:(1)調(diào)查研究物聯(lián)網(wǎng)視頻監(jiān)控技術(shù)現(xiàn)狀,分析其中存在的問題。提出基于RTSP轉(zhuǎn)發(fā)與Epiphany低功耗異構(gòu)多核架構(gòu)的“就地”處理物聯(lián)網(wǎng)嵌入式視頻中間件解決思路。(2)研究圖像視頻計(jì)算中廣泛應(yīng)用的基礎(chǔ)算法(矩陣運(yùn)算與DCT算法等)在異構(gòu)多核嵌入式平臺(tái)上的移植與實(shí)現(xiàn)。研究分析了多種主要并行編程模型:Epiphany SDK、MPI、Open MP、Open CL在Epiphany并行異構(gòu)多核架構(gòu)上的可編程性和性能。研究分析了核間通信對(duì)Epiphany架構(gòu)圖像視頻基礎(chǔ)算法性能的重要影響。(3)基于Epiphany架構(gòu)實(shí)現(xiàn)了一種VLC+DPM(VLC,Video LAN Client;DPM,Deformable Part Model)的視頻轉(zhuǎn)發(fā)與模式識(shí)別的物聯(lián)網(wǎng)嵌入式中間件,在研究圖像視頻計(jì)算基礎(chǔ)性算法的基礎(chǔ)上,分析DPM算法并將其移植到Epiphany架構(gòu)。通過高性能低功耗的嵌入式多核計(jì)算架構(gòu),實(shí)現(xiàn)物聯(lián)網(wǎng)前端視頻現(xiàn)場(chǎng)處理,完成視頻的處理與轉(zhuǎn)發(fā)。本文所提技術(shù)在功耗只有6.587瓦的嵌入式結(jié)點(diǎn)實(shí)現(xiàn)視頻監(jiān)控,實(shí)驗(yàn)結(jié)果表明512*512矩陣乘法的性能達(dá)到酷睿i7 2600計(jì)算機(jī)的處理水平,是一種低功耗、低成本的視頻實(shí)時(shí)中間件技術(shù),為減少視頻數(shù)據(jù)處理延遲,提高數(shù)據(jù)處理效率提供了有益的借鑒和參考。
[Abstract]:I video as an important source of modern data, its related technology is becoming increasingly important. Although video technology has been widely used in agriculture, industry, military, security, transportation and so on, there are still many problems to be solved in Internet of things video technology, such as the disunity of access interface and the weak computing and processing ability of front end. In most citation environments, video streams pass through perception layer, transmission layer to processing layer and then to application layer, usually accompanied by certain delay, which affects the real-time performance and processing efficiency of Internet of things video surveillance. In order to facilitate video forwarding, reduce the delay of video and image data processing, and improve the data transmission and processing efficiency of Internet of things, this paper presents an embedded video middleware technology based on RTSP(Real Time Streaming Protocol) protocol and "in-place" process in field. Through the low power, low cost, high performance embedded heterogeneous multi-core computing system to capture, process and forward the scene video, the main work of this paper includes: 1) investigating and researching the current situation of the Internet of things video surveillance technology. The existing problems are analyzed. Based on RTSP forwarding and Epiphany low power heterogeneous multi-core architecture, this paper puts forward the idea of "in-place" processing embedded video middleware in the Internet of things (IOT). The basic algorithms (matrix operation and DCT algorithm, etc.) which are widely used in image and video computing are studied. Transplantation and implementation on heterogeneous multi-core embedded platform. The programmability and performance of several main parallel programming models: Epiphany SDK / MPI Open Open Open CL on Epiphany parallel heterogeneous multicore architecture are studied and analyzed. This paper studies and analyzes the important influence of inter-core communication on the performance of the basic algorithm of image and video in Epiphany architecture. (3) based on the Epiphany architecture, a kind of embedded Internet of things middleware for video forwarding and pattern recognition is implemented, which is based on the Epiphany architecture. On the basis of studying the basic algorithm of image and video computing, the DPM algorithm is analyzed and transplanted to the Epiphany architecture. Through the embedded multi-core computing architecture with high performance and low power consumption, the front-end video field processing of the Internet of things is realized, and the video processing and forwarding are completed. The technology proposed in this paper realizes video surveillance at an embedded node with a power consumption of only 6.587 watts. The experimental results show that the performance of the 512 / 512 matrix multiplication is up to the processing level of the Core i7 2600 computer. It is a low power and low cost video real-time middleware technology. It provides a useful reference and reference for reducing the delay of video data processing and improving the efficiency of data processing.
【學(xué)位授予單位】：上海海洋大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN948.6;TP391.41

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