Extracting 3D urban models from oblique aerial images

Abstract

Oblique airborne cameras are increasingly used for area covering image collection of building facades in urban environments. Until recently, these images were mainly used to improve the visual appearance of relatively simple 3D building models by providing suitable facade texture. Meanwhile, oblique airborne images are also used to generate dense 3D point clouds using state-of-the-art pixel-based multi-stereo image matching. Subsequently, these point clouds can then enhance the amount of geometric and semantic detail of 3D urban models especially for the depicted building facades. However, occlusions and large view-point changes are especially demanding during dense image matching can be very challenging for oblique imagery in complex urban environment. As described in the paper, our matching pipeline tackles these problems by a coarse-to-fine modification of the SGM method. Furthermore the raw 3D point clouds are efficiently analyzed and filtered in subsequent steps, thus 3D data capture from oblique airborne imagery while aiming at the extraction of 3D urban models becomes feasible.