倾斜影像弥补了垂直摄影的不足，能够获取更多的地物信息，自动构建完整逼真的三维模型。但是，倾斜影像三维重建还存在一些问题：①棱角特征不够突出；②建筑物表面变形；③Mesh模型中存在孔洞等。因此，基于倾斜影像重建精细的Mesh模型仍然是一个研究难点：本项目提出顾及物方平面的密集匹配算法，针对城市区域地表建筑物，提高深度图的精度；然后，通过虚拟视角深度图融合方法去除点云噪声、提高精度以及有效减少计算冗余；最后，针对点云构建的初始Mesh模型是一个近似表面的问题，需要利用影像信息弥补Mesh重建过程中的信息损失，提出法向单参数法Mesh优化和顾及特征的正则项约束方法，构建精细Mesh模型，解决传统优化方法中自由度高、求导过程不严格、不能保持棱角特征和表面变形等问题。本项目研究的技术与方法适用于大区域、复杂场景的三维重建，具有较大的理论意义和实用价值，在大比例尺测图和城市规划等领域有广泛的应用前景。

Oblique photography can obtain more ground information, which makes up the weakness of the vertical photography and intuitively provides a realistic 3D model. But it still has some problems: ① the edge features of Mesh model are not prominent enough; ② the building surfaces are local deformed; ③ the Mesh model have holes etc. Therefore, it is still a difficult task that automatically constructs Mesh model based on the oblique images. In this project, a dense matching algorithm is proposed to improve the precision of the depth map for the buildings in the urban area. Then, using the proposed depth map fusion method based on the virtual perspective to remove the point cloud noise, improve the precision of the point cloud and effectively reduce the computational redundancy. Finally, the initial Mesh model constructed by point cloud usually reconstructs an approximate surface, which needs to make use of the image information to compensate for the information loss in the process of Mesh reconstruction. By using the proposed single parameter Mesh optimization algorithm and the regularized term constraint algorithm with feature constraints, a fine Mesh model is constructed to solve the problems of high degree of freedom, non-strict derivation process, weak edge feature and surface deformation in traditional methods. The technology and method studied in this project can be applied to 3D reconstruction of large area and complex scenes. It has great theoretical significance and practical value, and has a wide range of applications in large-scale mapping and urban planning.