本文選題：點云 + 特征點�。� 參考：《重慶師范大學(xué)》2013年碩士論文

【摘要】：隨著地理信息產(chǎn)業(yè)的快速發(fā)展，實施數(shù)字城市乃至數(shù)字地球戰(zhàn)略是信息化建設(shè)的重要組成部分，其中三維空間數(shù)據(jù)是建立數(shù)字化地球與智慧型城市的基礎(chǔ)與前提。為了提高三維空間數(shù)據(jù)采集效率，人們發(fā)明了三維激光掃描儀來快速獲取現(xiàn)實場景的三維點云數(shù)據(jù)，但也存在一些不足；為了解決激光掃描儀三維建模以及軟件三維建模方面存在的問題，并使得三維場景能夠具有繪制速度快、低成本以及真實感效果，人們提出了基于圖像的三維重建技術(shù)，由于輸入數(shù)據(jù)來源于現(xiàn)實場景二維圖像，因此降低了三維重建的復(fù)雜度，建模效率較高，但如何進一步提高三維建模精度仍然值得我們繼續(xù)研究。 采集二維圖像序列是三維地理場景進行重建工作的基礎(chǔ)，本研究采用四種不同的圖像采集方式獲取場景的二維圖像，其中每個采集方式的場景適用范圍與優(yōu)劣不同。首先，對獲取的二維圖像序列進行了預(yù)處理，包括圖像增強與圖像濾波處理兩方面，使用了MATLAB的編程實現(xiàn)了圖像的灰度轉(zhuǎn)換與均值濾波；其次，采用了Harris特征點提取算法對圖像中的特征點進行了提取，并分別在圖像全景和圖像局部區(qū)域兩種情形下進行了特征點之間的匹配，對匹配效果中的錯誤匹配與正確匹配進行了量化值分析；然后，從基于雙目視覺的三維點坐標估計角度，分別對雙目橫向模式、角度掃描模式和雙目縱向模式的三維坐標計算進行了分析，再將雙目視覺形式獲取三維點坐標擴展至多視點形式獲取三維點云，，多視點形式有效降低了圖像特征點匹配的不確定性，消除或減少圖像匹配引起的誤匹配；再次，對生成的原始點云進行優(yōu)化處理，使用了圖像的預(yù)先掩膜處理與立體點云框定優(yōu)化處理。本研究采用了三維點云的Delaunay三角剖分方法，得出了三維三角網(wǎng)格模型，并對三角網(wǎng)格模型進行了真實感紋理繪制，重建出了較為逼真的三維地理場景；最后，對不同圖像采集方式重建出的三維地理場景進行了研究總結(jié)與展望。
[Abstract]:With the rapid development of geographic information industry, the implementation of digital city and even digital earth strategy is an important part of information construction, in which three-dimensional spatial data is the foundation and premise for the establishment of digital earth and intelligent city. In order to improve the efficiency of 3D spatial data acquisition, 3D laser scanner has been invented to quickly acquire 3D point cloud data of real scene, but there are some shortcomings. In order to solve the problems in 3D modeling of laser scanner and 3D modeling of software, and to make 3D scene rendering fast, low cost and realistic effect, 3D reconstruction technology based on image is proposed. Since the input data is derived from the 2D images of the real scene, the complexity of 3D reconstruction is reduced and the modeling efficiency is high. However, how to further improve the accuracy of 3D modeling is still worthy of further study. The acquisition of 2D image sequences is the basis of 3D geographic scene reconstruction. In this study, four different image acquisition methods are used to obtain 2D images of the scene, in which the scope of application and the advantages and disadvantages of each acquisition method are different. Firstly, the two dimensional image sequences obtained are preprocessed, including image enhancement and image filtering, and the gray level conversion and mean filtering are realized by MATLAB programming. Harris feature point extraction algorithm is used to extract the feature points in the image, and the matching between the feature points in the panoramic image and the local region of the image is carried out respectively. The quantization value of mismatch and correct matching in matching effect is analyzed. Then, from the angle of 3D point coordinate estimation based on binocular vision, the binocular transverse pattern is analyzed. The calculation of 3D coordinates of angle scanning mode and binocular longitudinal mode is analyzed, and then the binocular visual form of acquiring 3D point coordinates is extended to multi-view form to obtain 3D point cloud. Multi-view form effectively reduces the uncertainty of image feature point matching, eliminates or reduces the mismatch caused by image matching. Thirdly, the original point cloud is optimized. Image premask processing and stereo point cloud block optimization are used. In this study, the Delaunay triangulation method of 3D point cloud is adopted, the 3D triangular mesh model is obtained, and the realistic texture of the triangulated mesh model is drawn to reconstruct the realistic 3D geographic scene. The three-dimensional geographic scene reconstructed by different image acquisition methods is summarized and prospected.
【學(xué)位授予單位】：重慶師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P208;TP391.41

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本文編號：1883071