本文選題：Android　切入點(diǎn)：三維點(diǎn)云重建　出處：《西北農(nóng)林科技大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：作物三維模型渲染是農(nóng)業(yè)信息化領(lǐng)域的研究熱點(diǎn)。目前,作物的三維模型渲染多數(shù)是基于PC端。但在智能設(shè)備迅速發(fā)展的今天,人們希望能夠在移動(dòng)端有良好的視覺體驗(yàn),因此本文通過對(duì)一些渲染算法移植,從而實(shí)現(xiàn)這一目標(biāo)。其中的關(guān)鍵問題是如何將這些算法進(jìn)行改進(jìn)使其適應(yīng)移動(dòng)端低帶寬、低功耗的需求。本研究以作物三維模型為研究對(duì)象,在詳細(xì)分析其原理、實(shí)現(xiàn)過程后,基于Android平臺(tái)結(jié)合OpenGL ES圖形庫實(shí)現(xiàn)了作物三維模型的渲染。主要內(nèi)容如下:(1)實(shí)現(xiàn)了作物三維點(diǎn)云的重建算法,獲取了三維模型。針對(duì)本設(shè)計(jì)輸入的點(diǎn)云是精簡去噪的點(diǎn)云,且其來自一個(gè)掃描設(shè)備或多個(gè)掃描設(shè)備的特點(diǎn),選取適合該三維點(diǎn)云的重建算法—貪婪投影算法對(duì)玉蘭樹和玉米植株等多種作物進(jìn)行重建,獲得了很好的重建效果。通過與泊松重建算法對(duì)比,針對(duì)植物等散亂葉片的點(diǎn)云數(shù)據(jù),雖然貪婪投影算法效率低于泊松重建算法約20.61%,但是能夠體現(xiàn)植物的拓?fù)浣Y(jié)構(gòu),而泊松重建雖然時(shí)間效率高,但出現(xiàn)冗余面。(2)實(shí)現(xiàn)了移動(dòng)端三維模型的顯示。針對(duì)三維模型如何在移動(dòng)端顯示的問題,本文采用了應(yīng)用廣泛的3D標(biāo)準(zhǔn)文件類型—STL文件保存獲取到的三維模型。使用OpenGL ES在Android Studio上實(shí)現(xiàn)三維模型的獲取,實(shí)驗(yàn)結(jié)果表明該讀取方式可以對(duì)STL文件讀取并顯示,且顯示位置自適應(yīng)于手機(jī)屏幕。(3)實(shí)現(xiàn)了以光照為核心的移動(dòng)端三維模型的渲染。針對(duì)模型不夠真實(shí),視覺效果不佳的問題,本文對(duì)模型進(jìn)行了局部光照處理和全局光照處理。局部光照處理采用Phong氏光照模型,很好的模擬了高光效果;全局光照處理采用光線跟蹤算法,很好的模擬了光照下的陰影效果。在網(wǎng)格面達(dá)到85436時(shí),移動(dòng)端依然可以實(shí)現(xiàn)渲染,渲染時(shí)間為36.24分。本文還對(duì)該方法進(jìn)行了功能性測(cè)試和普適性測(cè)試。實(shí)驗(yàn)基于斯坦福Bunny密集點(diǎn)云數(shù)據(jù)對(duì)該方法進(jìn)行功能性測(cè)試,選取八組數(shù)量不同的點(diǎn)云數(shù)據(jù)進(jìn)行渲染對(duì)比,測(cè)試用例表明模型表面的光滑程度會(huì)對(duì)渲染結(jié)果造成影響,當(dāng)點(diǎn)云數(shù)量少于3305時(shí),高光面有明顯的缺損;選取不同類型的三維模型進(jìn)行普適性測(cè)試,測(cè)試用例表明該方法可以實(shí)現(xiàn)多種模型的渲染。通過以上兩方面的測(cè)試,結(jié)果表明該方法實(shí)現(xiàn)了預(yù)期的功能,且能夠廣泛使用。
[Abstract]:Crop 3D model rendering is a hot topic in the field of agricultural informatization. At present, most of crop 3D model rendering is based on PC. However, with the rapid development of intelligent devices, people hope to have a good visual experience on mobile side. The key problem in this paper is how to adapt these algorithms to the low bandwidth on the mobile side. In this study, the three dimensional model of crop is taken as the research object, after the detailed analysis of its principle, the realization process, Based on Android platform and OpenGL es graphics library, the rendering of crop 3D model is realized. The main contents are as follows: 1) the reconstruction algorithm of crop 3D point cloud is realized, and the 3D model is obtained. The point cloud input in this design is a reduced denoising point cloud. Based on the characteristics of one or more scanning devices, the greedy projection algorithm, which is suitable for the 3D point cloud reconstruction, is selected to reconstruct magnolia and maize plants. Compared with Poisson's reconstruction algorithm, the greedy projection algorithm is less efficient than Poisson's reconstruction algorithm, but it can reflect the topological structure of plants, although the greedy projection algorithm is less efficient than Poisson's reconstruction algorithm. Poisson reconstruction has high time efficiency, but redundant surface. 2) realize the display of 3D model of mobile terminal. In view of the problem of how to display 3D model on mobile side, This paper adopts 3D standard file type -STL file which is widely used to save the acquired 3D model. We use OpenGL es to obtain 3D model on Android Studio. The experimental results show that the method can read and display the STL file. And the display position adapts to the mobile phone screen. 3) it realizes the rendering of the 3D model of the mobile end with illumination as the core. Aiming at the problem that the model is not real enough and the visual effect is not good, In this paper, the local illumination processing and the global illumination processing are carried out. The Phong illumination model is used in the local illumination processing, and the highlight effect is well simulated, and the global illumination processing is based on the ray-tracking algorithm. Very good simulation of the shadow effect under light. When the mesh surface reaches 85436, the mobile side can still render, The rendering time is 36.24 points. This paper also carries on the functional test and the universality test to this method. The experiment carries on the function test based on the Stanford Bunny dense point cloud data, selects eight groups of points cloud data to render the contrast, Test cases show that the smoothness of the surface of the model will affect the rendering results. When the number of point clouds is less than 3305, the high light surface has obvious defects. The test cases show that the method can be used to render multiple models. The results show that the proposed method achieves the expected function and can be widely used.
【學(xué)位授予單位】：西北農(nóng)林科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;TP316

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 董天琪;張志毅;;直接精簡密集點(diǎn)云的三角網(wǎng)格重建[J];計(jì)算機(jī)應(yīng)用與軟件;2016年06期

2 雷永慶;安仲強(qiáng);;三維重建光照模型介紹[J];電腦知識(shí)與技術(shù);2015年16期

3 劉慶科;;淺談利用三維掃描拓展數(shù)字媒體藝術(shù)[J];新西部(理論版);2014年14期

4 李世森;王熹芳;;凹包內(nèi)散亂點(diǎn)集Delaunay四面體角度剖分算法[J];水道港口;2014年02期

5 徐丹;;論三維掃描打印技術(shù)對(duì)文物保護(hù)的作用[J];數(shù)位時(shí)尚(新視覺藝術(shù));2014年02期

6 李昌領(lǐng);張虹;朱良峰;;含內(nèi)孔多面體的約束Delaunay四面體剖分算法[J];武漢大學(xué)學(xué)報(bào)(信息科學(xué)版);2014年03期

7 孔令麒;黎展榮;韋婷;魏為;;基于L系統(tǒng)的樹木建模與仿真[J];科學(xué)技術(shù)與工程;2013年32期

8 方芳;程效軍;;海量散亂點(diǎn)云快速壓縮算法[J];武漢大學(xué)學(xué)報(bào)(信息科學(xué)版);2013年11期

9 楊客;張志毅;董艷;;基于自適應(yīng)八叉樹分割點(diǎn)云的表面模型重建[J];計(jì)算機(jī)應(yīng)用與軟件;2013年06期

10 李紅波;吳亮亮;吳渝;;引入三維陰影及鏡面反射的兩步光源檢測(cè)算法[J];小型微型計(jì)算機(jī)系統(tǒng);2013年04期

相關(guān)碩士學(xué)位論文 前3條

1 黃龍;基于GLSL三維渲染效果的研究與應(yīng)用[D];西安科技大學(xué);2014年

2 劉紅偉;基于TLiDAR點(diǎn)云數(shù)據(jù)建立三維樹木模型[D];北京林業(yè)大學(xué);2011年

3 李琳;三維圖形引擎設(shè)計(jì)及其光影特效的研究與實(shí)現(xiàn)[D];電子科技大學(xué);2009年

，

本文編號(hào)：1640454