A Novel UAV View Planning Strategy for High Quality 3D Reconstruction of Irregular-Shaped Architecture

Zhenyu Liang, Zhaolun Liang, Mingzhu Wang, Liu Yang, Jack C. P. Cheng

Abstract: UAV-based 3D reconstruction has proven to be an effective technique for assessing the current state of architectures during the maintenance stage. Many buildings are designed with irregular shapes to fulfill aesthetic requirements. These buildings have lots of occlusion regions and edge regions, which makes it difficult for most commercially available flight planners to perform high-quality 3D reconstruction. To address this problem, we propose a novel UAV viewpoint generation strategy of 3D flight planning. Firstly, we detect the occlusion regions and edge regions through mesh analysis, devoid of any dependence on prior knowledge or deep-learning techniques. This makes our algorithm applicable to various scenes. Besides, we formulate the viewpoints optimization problem based on triangles in the mesh model with the consideration of two regions and MVS influence factors. Then we propose the SSA-variant algorithm to directly optimize the viewpoints’ location and orientation within a continuous flyable space. We validate our view planning strategy by assessing both the optimization convergence and reconstruction quality in a synthetic scene. The result shows that our SSA-variant algorithm performs higher convergency speed and accuracy than other optimization algorithms, such as GA and PSO. Compared to off-the-shelf flight planners and state-of-art 3D UAV path planning methods, images captured by our strategy can generate finer 3D reconstruction model for irregular-shaped architecture. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

External IDs:doi:10.1007/978-3-031-84208-5_42