City environments often lack textured areas, contain
repetitive structures, strong lighting changes and therefore
are very difficult for standard 3D modeling pipelines.
We present a novel unified framework for creating 3D city
models which overcomes these difficulties by exploiting image
segmentation cues as well as presence of dominant
scene orientations and piecewise planar structures. Given
panoramic street view sequences, we first demonstrate how
to robustly estimate camera poses without a need for bundle
adjustment and propose a multi-view stereo method which
operates directly on panoramas, while enforcing the piecewise
planarity constraints in the sweeping stage. At last, we
propose a new depth fusion method which exploits the constraints
of urban environments and combines advantages of
volumetric and viewpoint based fusion methods. Our technique
avoids expensive voxelization of space, operates directly
on 3D reconstructed points through effective kd-tree
represe...