## 1 Introduction  
With the rapid development of the social economy and the acceleration of urban information, the digital city has created the conditions for the harmonious development of cities, and the foundation of the digital city is a city with a three-dimensional (3D) model [1]. With the increasingly broad application of 3D GIS [2, 3], urban 3D models are widely used in urban maps, digital cities, and virtual campuses [4]. Three-dimensional reconstruction of oblique photogrammetry uses multiple optical sensors to collect data from the target area from multiple angles simultaneously, which can restore the structure of the ground object quickly and efficiently and attach the real texture so as to provide real scene information of the ground object. This effectively reduces the cost of modeling, especially in the field of 3D city construction [5] and has become one of the main means of city modeling [6]. At present, the 3D reconstruction technology of oblique photogrammetry is widely used in various fields, such as positioning services [7], disaster assessment [8], and archaeological research [9], taking advantage of its high efficiency, wide range, and strong sense of reality. The process of acquiring a 3D model by UAV includes the steps of acquiring aerial images, position and orientation system (POS) data and control point data in the field, automatically performing aerial triangulation and aerial triangulation encryption,dense matching, the construction of triangulation networks, and texture mapping [10]. The production process of an oblique photography 3D model is characterized by full automation, so the modeling quality is greatly affected by the oblique image. The 3D model is automatically constructed, it is only a continuous three-dimensional surface model of the overall scene without semantic topological relations [11], resulting in an incorrect structure of the 3D model that is inconsistent with the real scene, which is only suitable for simple applications such as macroscopic visual browsing of the overall scene, and cannot meet the needs of applications such as refined city management [12; 13]. The edge line is the most obvious part of the building. Whether the edge line is straight or not will directly affect the realism of the building. In many cases, the realism of the 3D building model and the requirements of further application analysis can be met only by restoring the edge line [14]. Regular edge lines can effectively improve the rendering effect and realism of building models. To restore the building edge line of a 3D model, the feature line of the edge line needs to be drawn. Currently, there are two main feature line extraction methods for existing 3D models: the surface-based extraction method and the edge-based extraction method. For the surface-based extraction method, there are mainly two types. One is by starting from multiple seed points; each seed point grows with the same curvature as that of the surface, and then the intersection line between these surfaces is calculated, with the obtained intersection line being the feature line [15; 16; 17]. The other is to extract feature points and feature edges by calculating the curvature of local areas on the model surface and then connecting them through certain methods to obtain complete feature lines [18; 19]. Surface-based feature extraction methods rely heavily on noise-sensitive differential invariants such as surface curvature [20], so these methods are generally only applicable to smooth 3D models with relatively uniform points and faces, which are generally constructed manually. It is difficult to take into account the small noise in complex and rough 3D models of oblique photogrammetry using this type of method. Because of the large computation and low speed, it is also difficult to extract the feature lines of a model quickly. The extracted results are not based on the edges of the existing triangles, so it is not convenient for use in directly restoring the 3D model of oblique photogrammetry [21].