​Aerial 3D Building Reconstruction from RGB Drone Imagery

3D Building Reconstruction is an important problem with applications in urban planning, emergency response,
and disaster planning. This paper presents a new pipeline for 3D reconstruction of buildings from RGB imagery
captured via a drone. We leverage the commercial software Pix4D to construct a 3D point cloud from RGB
drone imagery, which is then used in conjunction with image processing and geometric methods to extract a
building footprint. The footprint is then extruded vertically based on the heights of the segmented rooftops.
The footprint extraction involves two main steps, line segment detection and polygonization of the lines. To
detect line segments, we project the point cloud onto a regular grid, detect preliminary lines using the Hough
transform, refine them via RANSAC, and convert them into line segments by checking the density of the points
surrounding the line. In the polygonization step, we convert detected line segments into polygons by constructing
and completing partial polygons, and then filter them by checking for support in the point cloud. The polygons
are then merged based on their respective height profiles. We have tested our system on two buildings of several
thousand square feet in Alameda, CA, and obtained an F1 score of 0.93 and 0.95 respectively as compared to
the ground truth.