【摘要】 随着计算机技术的快速发展,基于图像的建筑物三维重建逐渐成为计算机图形学和计算机视觉领域的研究热点之一.由于建筑物图像背景复杂、序列长且杂乱无序,现有的三维重建算法存在耗时长、局部几何细节重建效果差的问题.文中针对这些不足提出了一种基于图像匹配实现点云融合的建筑物立面三维重建算法.首先寻找新添加的建筑物局部图像在原始图像集中的匹配图像,组成规模较小的图像集并重建出局部点云模型,然后通过匹配不同点云模型在同一幅图像上的投影点,找到点云模型之间的一致对应点集,接着求解点云集合之间的最佳对齐变换,实现整体和局部点云模型的融合,最终生成建筑物立面完整的三维模型.实验表明,采用文中算法进行三维重建,可以有效地减少重建时间,提高重建精度.更多还原

【Abstract】 With the rapid development of computer technology,image-based 3D building reconstruction has become a hot topic in the fields of computer graphics and computer stereo vision.Because the backgrounds of building images are typically complicated,and the sequence is very long and disorderly,existing 3D reconstruction algorithms will take a lot of time to obtain the 3D model,and possibly get poor results in the local areas.This paper proposes a novel 3D building facade reconstruction algorithm based on image matching and point cloud fusing to address those problems.Firstly,we find the best matching images in the additional new image set.Secondly,we get the 2D projection points of the 3D point cloud on the same image.The 3D points corresponding to the same 2D projection points are collected for 3D point cloud fusing.Thirdly,based on the derived 3D corresponding points,we compute the best alignment transformation between the point sets such that they can match with each other with minimum error.Finally,we merge the two point clouds with the computed best transformation to get the complete building facade model.Experiments show that our method can take much less time to reconstruct the building facade,and improve the precision as well.更多还原