Abstract
Abstract. Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs) images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM) is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.
Highlights
There are various applications of 3D building modelling such as urban mapping, virtual reality, 3D visualization, and analysing
Many methods and techniques are developed in computer vision and photogrammetric domains to reconstruct the structure of buildings which can be categorized based on different aspects of modelling such as level of details (LOD), automation levels, the input data (3D or 2D), and the 3D modelling approaches (model driven and data driven (Tarsha-Kurdi, et al, 2007))
According to the proposed workflow (Figure 1), the first step is dedicated to improve the accuracy of pose parameters and to calculate 3D coordinates using some corresponding features of images, ground control points and initial pose parameters in an Automatic Aerial Triangulation (AAT) and Bundle Block Adjustment (BBA) solution
Summary
There are various applications of 3D building modelling such as urban mapping, virtual reality, 3D visualization, and analysing. A semiautomatic modelling was proposed by (Cheng, et al, 2011) based on a new dynamic selection strategy and K-means clustering to identify the 3D boundaries of buildings In this method, the region-growing algorithm based on the RANSAC plane-fitting technique is employed for 3D building model reconstruction with high-correctness, high-completeness, and good geometric accuracy (Cheng, et al, 2011). A fully automatic reconstructions of complex buildings can be achieved using both point cloud and close range images and based on a set of geometric primitives, like planes or cylinders. This method include three steps such as camera orientation, image segmentation, and image-based modelling (Reisner Kollmann, 2013). A semiautomatic method based on the extracted point cloud from multi view images is investigated to generate the 3D model of building structures’ details
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
