Authors:
Steffen Goebbels
and
Regina Pohle-Fröhlich
Affiliation:
Niederrhein University of Applied Sciences, Germany
Keyword(s):
Point Cloud Registration, Linear Programming, Structure from Motion, Building Reconstruction, CityGML.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Geometry and Modeling
;
Image and Video Analysis
;
Image Registration
;
Image-Based Modeling
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Software Engineering
;
Stereo Vision and Structure from Motion
Abstract:
This paper describes a method to align photogrammetric point clouds with CityGML 3D city models. Amongst
others, we use photogrammetric point clouds that are generated from videos taken from the driver’s perspective
of a car. Clouds are computed with the Structure-from-Motion algorithm. We detect wall planes to rotate these
clouds so that walls become vertical. This allows us to find buildings’ footprints by accumulating points that
are orthogonally projected to the ground. Thus, the main alignment step can be performed in 2D. To this end,
we match detected footprints with corresponding footprints of CityGML models in a x-y-plane based on line
segments. These line segments are detected using a probabilistic Hough transform. Then we apply a Mixed
Integer Linear Program to find a maximum number of matching line segment pairs. Using a Linear Program,
we optimize a rigid affine transformation to align the lines of these pairs. Finally, we use height information
along CityGML ter
rain intersection lines to estimate scaling and translation in z-direction. By combining the
results, we obtain an affine mapping that aligns the point cloud with the city model. Linear Programming is
not widely applied to registration problems; however the technique presented is a fast alternative to Iterative
Closest Point algorithms that align photogrammetric point clouds with clouds sampled from city models.
(More)