Fast Robust Large-scale Mapping from Video and Internet Photo ...

struction. By contrast, we view summarization as an image organization step
that precedes 3D reconstruction, and we take advantage of the observation
that a good subset of representative or “iconic” images can be obtained using
relatively simple 2D appearance-based techniques [29, 33].
Given that [34, 35] provide excellent surveys on the work on binocular
or multiple-view stereo we refer the reader to these articles. Our system
for reconstruction from video streams extends the idea by Collins [36] to
dense geometry estimation. This approach permits an efficient execution
on the GPU as proposed originally by Yang and Pollefeys [37]. There has
been a number of approaches proposed to specifically target urban environments
using mainly the fact that they predominantly consist of planar
surfaces [38, 39, 40], or even more strict orthogonality constraints [41]. To
ensure computational feasibility large-scale systems generate partial reconstructions,
which are afterwards merged into a common model. Conflicts
and errors in the partial reconstructions are identified and resolved during
the merging process. Most approaches so far target data produced by range
finders, where noise levels and the fraction of outliers are typically significantly
lower than those of passive stereo. Turk and Levoy [42] proposed to
remove the overlapping mesh parts after registering the triangular meshes.
A similar approach was proposed by Soucy and Laurendeau [43]. Volumetric
model merging was proposed by Hilton et al. [44], Curless and Levoy [45],
which was later extended by Wheeler et al. [46]. Koch et al. [47] presented a
volumetric approach for fusion as part of an uncalibrated 3D modeling system.
Given depth maps for all images, the depth estimates for all pixels are
projected in the voxelized 3D space. Each depth estimate votes for a voxel in
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