本文選題：點(diǎn)云 + 預(yù)處理��； 參考：《安徽建筑大學(xué)》2017年碩士論文

【摘要】：曲面重構(gòu)技術(shù)在逆向工程、機(jī)器視覺、虛擬現(xiàn)實(shí)VR(Virtual Reality)、現(xiàn)代醫(yī)療等多個領(lǐng)域中被廣泛使用。隨著三維激光掃描技術(shù)的飛速發(fā)展和日益成熟,可通過三維激光掃描技術(shù)來獲取古建筑物表面高密度的三維點(diǎn)云數(shù)據(jù)信息,再通過后期的分割優(yōu)化、濾波去噪、法線計(jì)算、曲面重構(gòu)等操作完成對點(diǎn)云數(shù)據(jù)的三維建模。由于支持曲面重構(gòu)的軟件多存在操作復(fù)雜、交互定義過多、對輸入數(shù)據(jù)要求過于嚴(yán)苛等問題至今未得到廣泛推廣。然而,對古建筑進(jìn)行三維建模的通常做法是前期通過人工測量得到建筑物中各個構(gòu)件的具體物理參數(shù),后期再借助三維建模軟件等方式進(jìn)行描繪、貼圖等,最終效果不夠真實(shí)且誤差較大。通過對徽派建筑中大小構(gòu)件進(jìn)行考察,本課題最終選用了徽派建筑所特有的穿斗抬梁式木構(gòu)架、門樓和欄桿作為研究對象從而展開研究。論文圍繞徽派建筑構(gòu)件點(diǎn)云的曲面重構(gòu)系統(tǒng)研究主要探討了以下三方面問題:第一,點(diǎn)云數(shù)據(jù)預(yù)處理工作。論文以徽派建筑所特有的穿斗抬梁式木構(gòu)架為例,對其進(jìn)行多站點(diǎn)掃描獲得原始點(diǎn)云數(shù)據(jù)。首先,通過改進(jìn)的迭代最近點(diǎn)算法(簡稱ICP算法,Iterative Closet Point)對多站點(diǎn)云數(shù)據(jù)進(jìn)行配準(zhǔn)拼接,獲得整棟建筑物點(diǎn)云數(shù)據(jù);其次,對配準(zhǔn)后點(diǎn)云數(shù)據(jù)使用隨機(jī)采樣一致性算法進(jìn)行分割優(yōu)化,獲得梁柱點(diǎn)云數(shù)據(jù);最后,利用體素網(wǎng)格化法對梁柱點(diǎn)云數(shù)據(jù)中離群點(diǎn)進(jìn)行采樣,再通過濾波器Statistical OutlierRemoval對離群點(diǎn)進(jìn)行剔除操作。第二,基于預(yù)處理后點(diǎn)云數(shù)據(jù)的曲面重構(gòu)。通過使用最小二乘法對預(yù)處理后點(diǎn)云數(shù)據(jù)進(jìn)行直接地法線估計(jì)推斷,得到梁柱點(diǎn)云數(shù)據(jù)中每一點(diǎn)的法線及其正負(fù)向。借助點(diǎn)云庫PCL(Point Cloud Library)開源平臺,分別使用貪婪投影三角化算法、BallPivoting算法以及泊松算法對經(jīng)過預(yù)處理且具有法線的梁柱點(diǎn)云數(shù)據(jù)進(jìn)行曲面重構(gòu)并同時給出了核心算法步驟,最終得到每種算法相對應(yīng)的效果圖及參數(shù)信息。第三,曲面重構(gòu)結(jié)果對比。通過對比三種算法在同一構(gòu)件點(diǎn)云條件下的曲面重構(gòu)效果圖以及網(wǎng)格面數(shù)、網(wǎng)格頂點(diǎn)數(shù)、孔洞數(shù)、耗時等參數(shù)信息,結(jié)果表明泊松算法最終效果圖要明顯優(yōu)于其它兩種方法,尤其是最終結(jié)果中沒有孔洞出現(xiàn),這對于曲面重構(gòu)最終三維模型的完整性輸出至關(guān)重要。以上研究借助三維激光掃描技術(shù)獲取被測對象的點(diǎn)云原始數(shù)據(jù),通過多邊形網(wǎng)格化等技術(shù)實(shí)現(xiàn)點(diǎn)云數(shù)據(jù)的分割、濾波、法線估計(jì)等預(yù)處理操作,最終建立基于泊松算法的徽派建筑構(gòu)件點(diǎn)云數(shù)據(jù)曲面重構(gòu)模型。文中所提曲面重構(gòu)整套研究方案為三維建模技術(shù)在建筑中的應(yīng)用尤其是在古建筑復(fù)建、數(shù)字化等領(lǐng)域中提供了新的研究思路。
[Abstract]:Surface reconstruction is widely used in many fields such as reverse engineering, machine vision, virtual reality VR(Virtual reality, modern medicine and so on. With the rapid development and maturity of 3D laser scanning technology, 3D laser scanning technology can be used to obtain high density 3D point cloud data information on the surface of ancient buildings, and then through the later segmentation optimization, filtering and denoising, normal calculation, Surface reconstruction and other operations complete the 3D modeling of point cloud data. Due to the complexity of operation, the definition of interaction and the strict requirement of input data, the software supporting surface reconstruction has not been widely popularized up to now. However, the common method of 3D modeling of ancient buildings is to obtain the physical parameters of each component by manual measurement in the early stage, and to depict them in the later stage by means of 3D modeling software, such as mapping, mapping, and so on. The final effect is not real and the error is large. Through the investigation of the large and small components in the Huizhou architecture, this topic finally selects the unique wooden frame of the bucket lift beam, the gatehouse and the railing as the research object to carry out the research. This paper mainly discusses the following three problems about the surface reconstruction system of Huizhou architectural component point cloud: first, point cloud data preprocessing. Taking Huizhou architecture as an example, the original point cloud data is obtained by multi-site scanning. Firstly, the improved iterative nearest point algorithm (ICP algorithm) is applied to the registration of multi-site cloud data to obtain the whole building point cloud data. After registration point cloud data is segmented and optimized by random sampling consistency algorithm to obtain Liang Zhu point cloud data. Finally, we use voxel mesh method to sample outliers in Liang Zhu point cloud data. Then the outliers are removed by filter Statistical OutlierRemoval. Second, surface reconstruction based on pre-processing point cloud data. By using the least square method to infer directly the normals of pre-processed point cloud data, the normals and their positive and negative directions of each point in Liang Zhu's point cloud data are obtained. With the help of point cloud library PCL(Point Cloud library open source platform, the greedy projection triangulation algorithm BallPivoting algorithm and Poisson algorithm are used to reconstruct the surface of preprocessed and normal Liang Zhu point cloud data, and the core algorithm steps are given. Finally, the corresponding effect diagram and parameter information of each algorithm are obtained. Third, the surface reconstruction results are compared. By comparing the surface reconstruction results of the three algorithms under the same component point cloud condition, as well as the grid surface number, the number of mesh vertices, the number of holes, the time consuming and so on, the results show that the Poisson algorithm is better than the other two methods in the final effect graph. In particular, there are no holes in the final results, which is very important for the integrity output of the final 3D model reconstruction. The above research uses 3D laser scanning technology to obtain the original point cloud data of the measured object, and realizes the preprocessing operations such as point cloud data segmentation, filtering, normality estimation and so on through polygonal gridding technology. Finally, the point cloud data surface reconstruction model based on Poisson algorithm is established. The whole research scheme of surface reconstruction in this paper provides a new research idea for the application of 3D modeling technology in architecture, especially in the field of reconstruction and digitization of ancient buildings.
【學(xué)位授予單位】：安徽建筑大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TU198;P225.2

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 胡絲蘭;周明全;稅午陽;武仲科;;一種改進(jìn)Ball Pivoting的散亂點(diǎn)云數(shù)據(jù)重建算法[J];系統(tǒng)仿真學(xué)報(bào);2015年10期

2 曾鋒;楊通;姚山;;點(diǎn)云重構(gòu)三角網(wǎng)格的生長型神經(jīng)氣算法[J];軟件學(xué)報(bào);2013年03期

3 程效軍;何桂珍;;適用于多值曲面修復(fù)的空洞邊界提取方法及應(yīng)用[J];測繪學(xué)報(bào);2012年06期

4 于榮歡;鄧寶松;吳玲達(dá);瞿師;;三維標(biāo)量場并行等值面提取與繪制技術(shù)[J];計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào);2012年02期

5 王莫;;三維激光掃描技術(shù)在故宮古建筑測繪中的應(yīng)用研究[J];故宮博物院院刊;2011年06期

6 王建文;杜春梅;;三維激光掃描系統(tǒng)的關(guān)鍵性技術(shù)研究[J];計(jì)算機(jī)工程與設(shè)計(jì);2010年05期

7 劉金玲;唐棣;;基于泊松方程實(shí)現(xiàn)點(diǎn)云的表面重構(gòu)[J];計(jì)算機(jī)應(yīng)用與軟件;2009年04期

8 周克勤;趙煦;丁延輝;;基于激光點(diǎn)云的3維可視化方法[J];測繪科學(xué)技術(shù)學(xué)報(bào);2006年01期

9 李家才;反求工程中一種數(shù)據(jù)平滑的方法[J];機(jī)械與電子;2005年11期

10 李必軍,方志祥,任娟;從激光掃描數(shù)據(jù)中進(jìn)行建筑物特征提取研究[J];武漢大學(xué)學(xué)報(bào)(信息科學(xué)版);2003年01期

相關(guān)博士學(xué)位論文 前1條

1 莫X;基于隱式函數(shù)的曲面重構(gòu)方法及其應(yīng)用[D];華中科技大學(xué);2010年

相關(guān)碩士學(xué)位論文 前9條

1 李志華;基于邊界曲線的細(xì)分曲面控制網(wǎng)格的生成方法研究[D];上海交通大學(xué);2015年

2 劉歡;DEM數(shù)據(jù)的預(yù)處理與三維重建算法研究[D];北京化工大學(xué);2014年

3 羅誠;基于復(fù)雜約束的稀疏點(diǎn)云空間曲面重構(gòu)方法與實(shí)現(xiàn)[D];電子科技大學(xué);2014年

4 張凱;基于泊松方程的三維表面重建算法的研究[D];河北工業(yè)大學(xué);2014年

5 張飛飛;點(diǎn)云數(shù)據(jù)簡化及三維曲面重構(gòu)[D];吉林大學(xué);2012年

6 周華偉;地面三維激光掃描點(diǎn)云數(shù)據(jù)處理與模型構(gòu)建[D];昆明理工大學(xué);2011年

7 李競超;基于立體視覺的三維重建[D];北京交通大學(xué);2010年

8 肖華;網(wǎng)格重構(gòu)及特征提取技術(shù)研究[D];浙江大學(xué);2010年

9 戴靜蘭;海量點(diǎn)云預(yù)處理算法研究[D];浙江大學(xué);2006年

，

本文編號：1834335