Abstract
In the reconstruction of façade elements, the identification of specific object types remains challenging and is often circumvented by rectangularity assumptions or the use of bounding boxes. We propose a new approach for the reconstruction of 3D façade details. We combine MLS point clouds and a pre-defined 3D model library using a BoW concept, which we augment by incorporating semi-global features. We conduct experiments on the models superimposed with random noise and on the TUM-FAÇADE dataset. Our method demonstrates promising results, improving the conventional BoW approach. It holds the potential to be utilized for more realistic facade reconstruction without rectangularity assumptions, which can be used in applications such as testing automated driving functions or estimating façade solar potential.
Abstract (translated)
在外墙元素的重构中，确定具体物体类型仍然具有挑战性，并且通常通过矩形性假设或使用边界框来规避。我们提出了一种新的外墙细节重构方法。我们通过结合MLS点云和预定义的3D模型库，使用BW概念进行增强，并引入半全局特征。我们在包含随机噪声的外模型的实验和TUM-FAÇADE数据集上进行了实验。我们的方法取得了很好的结果，改善了传统的BW方法。它具有在不考虑矩形性假设的情况下进行更真实外墙重构的潜力，可以应用于自动驾驶功能的测试或估计外墙太阳能潜力等应用。
URL
https://arxiv.org/abs/2402.06521
