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摘要: 倾斜摄影测量进行三维模型重建时,由于影像匹配精度和密集点云简化等因素,使得三角形网格模型表面的法向量存在许多明显噪声,加上镜头畸变和光照条件不同引起的影像间几何与辐射的不一致,最终导致不同三角形之间纹理映射结果不连续,这种碎片状纹理表面的真实感不强,难以直观理解。针对此,提出了一种局部区域表面一致性约束的纹理映射方法,采用区域生长策略将多个三角形合并为一个较大的平面区域,并且在区域生长过程中顾及了区域的连续性和平面性,建立该平面区域与同一影像之间的映射关系。实验证明了该方法能够有效消除纹理映射碎片化的现象。Abstract: Due to the limitations of the accuracies in dense image matching and the factors of simplification during the three dimensional mesh generation, enormous noises normally occur on the triangular mesh surfaces during object reconstruction procedures. Furthermore, the geometrical and radiant differences between images, together with the noises, cause the textured mesh fragmentation. Aiming to solve this problem, this paper proposes a texture mapping method using a local surface consistency constraint. In this mapping procedure, fragmented triangles are merged into a relative larger surface with region growing, considering continuity and planarity. The regions are treated as a rigid surface and mapped to the same image to relieve the fragmented effect in the textured mesh. Experimental results show that the proposed method is effective and the output has better consistency than industry standard software such as street factory.
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Keywords:
- oblique photogrammetry /
- triangle-mesh model /
- region-growing /
- texture mapping
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表 1 区域生长前后碎片化程度对比
Table 1 Comparison of Fragmentation Degrees of the One-by-one Approach and Our Approach
方法 总连通区域个数 三角形个数<10的连通区域个数 三角形个数<5的连通区域个数 三角形个数=1的连通区域个数 平均包含的三角形个数 逐个三角形映射方法 11 755 10 766 9 640 5 748 5.1 一致性约束的区域生长方法 909 541 457 216 66.0 -
[1] 朱庆, 徐冠宇, 杜志强, 等. 倾斜摄影测量技术综述[OL]. http://www.paper.edu.cn/releasepaper/content/201205-355,2012 Zhu Qing, Xu Guanyu, Du Zhiqiang, et al. Review of Oblique Photogrammetric Technology[OL]. http://www.paper.edu.cn/releasepaper/content/201205-355,2012
[2] 王伟, 黄雯雯, 镇姣. Pictometry倾斜摄影技术及其在3维城市建模中的应用[J]. 测绘与空间地理信息, 2011, 34(3):181-183 http://www.cnki.com.cn/Article/CJFDTOTAL-DBCH201103061.htm Wang Wei, Huang Wenwen, Zhen Jiao. Pictometry Oblique Photography Technique and Its Application in 3D City Modeling[J]. Geomatics & Spatial Information Technology,2011,34(3):181-183 http://www.cnki.com.cn/Article/CJFDTOTAL-DBCH201103061.htm
[3] Szeliski R. Video Mosaic for Virtual Environments[J]. IEEE Computer Graphics and Applications, 1996, 16(2):22-30 doi: 10.1109/38.486677
[4] 李治江, 张祖勋, 张剑清. 三维重建中真实纹理再现的一种有效方法[J]. 地理空间信息, 2004, 2(6):34-36 http://www.cnki.com.cn/Article/CJFDTOTAL-DXKJ200406011.htm Li Zhijiang, Zhang Zuxun, Zhang Jianqing. Effective Method on Realistic Texture Rendition in Three Dimension Reconstruction[J]. Geospatial Information, 2004,2(6):34-36 http://www.cnki.com.cn/Article/CJFDTOTAL-DXKJ200406011.htm
[5] 郭玲, 王建宇, 黄炎焱. 真实感3D重建中的纹理映射技术[J].中国图象图形学报, 2007, 12(10):1881-1884 http://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB200710046.htm Guo Ling, Wang Jianyu, Huang Yanyan. On Texture Mapping for Realistic 3D Reconstruction[J]. Journal of Image and Graphics, 2007,12(10):1881-1884 http://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB200710046.htm
[6] Allène C, Pons J P, Keriven R.Seamless Image-Based Texture Atlases Using Multi-band Blending[C]. 19th International Conference on Pattern Recognition, Tampa, Florida, USA, 2008
[7] Brown M, Lowe D G. Automatic Panoramic Image Stitching Using Invariant Features[J]. International Journal of Computer Vision, 2007,74(1):59-73 doi: 10.1007/s11263-006-0002-3
[8] 郑顺义, 周漾. 结构光系统结合数码相机的小物体高质量纹理重建[J]. 武汉大学学报·信息科学版, 2012, 37(5):529-534 http://ch.whu.edu.cn/CN/abstract/abstract195.shtml Zheng Shunyi, Zhou Yang. High Quality Texture Reconstruction for Small Objects Based on Structure Light Scanning System with Digital Camera[J]. Geomatics and Information Science of Wuhan University, 2012,37(5):529-534 http://ch.whu.edu.cn/CN/abstract/abstract195.shtml
[9] 周漾, 郑顺义, 黄荣永,等. 面泊松融合结合色彩变换的无缝纹理辐射处理[J]. 中国图象图形学报, 2014, 19(4):512-519 http://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201404003.htm Zhou Yang, Zheng Shunyi, Huang Rongyong,et al. Face-wise Poisson Blending with Color Transfor in Seamless Texturing[J]. Journal of Image and Graphics,2014,19(4):512-519 http://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201404003.htm
[10] 龚俊, 朱庆, 张叶廷,等. 顾及多细节层次的三维R树索引扩展方法[J]. 测绘学报, 2011, 40(2):249-255 http://www.cnki.com.cn/Article/CJFDTOTAL-CHXB201102022.htm Gong Jun, Zhu Qing, Zhang Yeting, et al. An Efficient 3D R-tree Extension Method Concerned with Levels of Detail[J]. Acta Geodaetica et Cartographica Sinica,2011,40(2):249-255 http://www.cnki.com.cn/Article/CJFDTOTAL-CHXB201102022.htm
[11] Yen S H, Hsieh Y J. A KD-Tree-Based Nearest Neighbor Search for Large Quantities of Data[J]. Transactions on Internet and Information Systems, 2013, 7(3):459-470 doi: 10.3837/tiis.2013.03.003
[12] Yuan Zhengwu, Wang Yuanhui. Research on K Nearest Neighbor Non-parametric Regression Algorithm Based on KD-Tree and Clustering Analysis[C]. 2012 Fourth International Conference on Computational and Information Sciences, Chongqing. China, 2012
[13] Matei B C, Sawhney H S. Building Segmentation for Densely Built Urban Regions Using Aerial LiDAR Data[C]. 2008 IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska, USA, 2008