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Automatic Occlusion Removal from Facades for 3D Urban Reconstruction Host Publication: LNCS Authors: C. Engels, T. David, V. Mathias, T. Tuytelaars, H. Sahli and L. Van Gool UsePubPlace: Berlin / Heidelberg Publisher: Springer Verlag Publication Year: 2011 Number of Pages: 12 ISBN: 978-3-642-23687-7
Abstract: Object removal and inpainting approaches typically require
a user to manually create a mask around occluding objects. While creating
masks for a small number of images is possible, it rapidly becomes
untenable for longer image sequences. Instead, we accomplish this step
automatically using an object detection framework to explicitly recognize
and remove several classes of occlusions. We propose using this technique
to improve 3D urban reconstruction from street level imagery, in
which building facades are frequently occluded by vegetation or vehicles.
By assuming facades in the background are planar, 3D scene estimation
provides important context to the inpainting process by restricting input
sample patches to regions that are coplanar to the occlusion, leading to
more realistic final textures. Moreover, because non-static and reflective
occlusion classes tend to be difficult to reconstruct, explicitly recognizing
and removing them improves the resulting 3D scene.
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