Université Paris-Est, Institut Géographique National, 73 avenue de Paris, 94160 Saint-Mandé cedex, France.
Sensors (Basel). 2011;11(1):228-59. doi: 10.3390/s110100228. Epub 2010 Dec 28.
This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach.
本文提出了一种基于模型的方法，用于从航空图像中重建 3D 多面体建筑模型。所提出的方法利用了平面结构透视投影产生的一些几何和光度特性。数据由校准的航空图像提供。该方法的新颖之处在于其无特征性和基于图像原始亮度的直接优化。所提出的框架避免了特征提取和匹配。3D 多面体模型是通过优化一个目标函数来直接估计的，该函数结合了基于图像的不相似性度量和多个航空图像上的梯度得分。优化过程通过差分进化算法进行。与基于特征的方法相比，所提出的方法旨在提供更准确的 3D 重建。快速的 3D 模型校正和更新可以利用所提出的方法。来自真实和合成图像的多个结果和性能评估表明了所提出方法的可行性和鲁棒性。
