本文選題：物聯(lián)網(wǎng) + 大數(shù)據(jù)��； 參考：《北京交通大學》2014年碩士論文

【摘要】：隨著智能時代的到來,在物聯(lián)網(wǎng)市場發(fā)展和大數(shù)據(jù)內(nèi)在需求的推動下,作為視覺傳感網(wǎng)中基礎節(jié)點的智能相機愈發(fā)顯現(xiàn)出其重要的科研和市場價值。本文在介紹了智能相機基本概念的基礎上,針對其獨立嵌入式系統(tǒng)的本質(zhì)和資源受限的特點提出了在智能相機設計研發(fā)過程中需要分析和解決的四個問題。然后,通過對這四個問題的逐步分析和解決,以低功耗、高性能、高靈活度和低成本為目標,我們提出并設計了一款基于FPGA的智能相機,并將其命名為Smart-Eyes。 目前,Smart-Eyes有兩個版本： 基礎版本Smart-Eyes (V1.0)具備了智能相機的完整框架和基本功能,能進行視頻圖像的實時采集、存儲、處理、傳輸和顯示,分辨率為720x576,幀率為25fps,總功耗大約4.4W。能同時基于DVI接口和以太網(wǎng)接口進行傳輸和顯示。 優(yōu)化版本Smart-Eyes(V2.0)在基礎版本之上,通過小型化降低能耗,采用分層結(jié)構(gòu)提高靈活性,實現(xiàn)雙目立體視覺系統(tǒng)增強智能化。根據(jù)仿真結(jié)果顯示,對于Middlebury提供的標準測試集Tsukuba,雙目匹配的算法速率可以達到60fps,平均誤點率約為11.3%,在保證實時性的前提下,以合理的硬件資源實現(xiàn)了具有一定準確率的雙目立體匹配,取得了算法執(zhí)行速度、匹配準確率和系統(tǒng)硬件資源的很好折衷。
[Abstract]:With the arrival of the intelligent age, with the development of the Internet of things market and the internal demand of big data, the intelligent camera, as the basic node in the vision sensor network, has more and more important scientific research and market value. Based on the introduction of the basic concept of intelligent camera, four problems need to be analyzed and solved in the process of intelligent camera design and development are put forward in view of the nature of independent embedded system and the limited resources. Then, by analyzing and solving these four problems step by step, aiming at low power consumption, high performance, high flexibility and low cost, we propose and design a smart camera based on FPGA and name it Smart-Eyes. There are currently two versions of Smart-Eyes: The basic version of Smart-Eyes V1.0) has the complete frame and basic function of the intelligent camera. It can capture, store, process, transmit and display the video image in real time. The resolution is 720x576, the frame rate is 25fps. the total power consumption is about 4.4w. Can be based on both DVI interface and Ethernet interface for transmission and display. Based on the basic version, the optimized version Smart-Eyesi V2.0 can reduce energy consumption by miniaturization, improve flexibility by adopting layered structure, and realize the enhancement of intelligence of binocular stereoscopic vision system. The simulation results show that for Tsukuba standard test set provided by Middlebury, the algorithm speed of binocular matching can reach 60fps. the average delay rate is about 11.3. The binocular stereo matching with certain accuracy is realized with reasonable hardware resources, and a good tradeoff between algorithm execution speed, matching accuracy and system hardware resources is obtained.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TB852.1

【參考文獻】

相關期刊論文 前9條

1 孫其博;劉杰;黎，

本文編號：1886030