NDLI: Parameter-free/Pareto-driven procedural 3D reconstruction of buildings from ground-level sequences

Content Provider	IEEE Xplore Digital Library
Author	Simon, L. Teboul, O. Koutsourakis, P. Van Gool, L. Paragios, N.
Copyright Year	2012
Description	Author affiliation: Center for Visual Computing, Ecole Centrale Paris (Simon, L.; Teboul, O.; Koutsourakis, P.; Paragios, N.) \|\| BIWI, ETH Zurich (Van Gool, L.)
Abstract	In this paper we address multi-view reconstruction of urban environments using 3D shape grammars. Our formulation expresses the solution to the problem as a shape grammar parse tree where both the tree and the corresponding derivation parameters are unknown. Besides the grammar constraint, the solution is guided by an image support that is twofold. First, we seek for a derivation that induces optimal semantic partitions in the different views. Second, using structure-from-motion, noisy depth maps can be determined towards minimizing their distance from to the ones predicted by any potential solution. We show how the underlying data structure can be efficiently optimized using evolutionary algorithms with automatic parameter selection. To the best of our knowledge, it is the first time that the multi-view 3D procedural modeling problem is tackled. Promising results demonstrate the potentials of the method towards producing a compact representation of urban environments.
Starting Page	518
Ending Page	525
File Size	673601
Page Count	8
File Format	PDF
ISBN	9781467312264
ISSN	10636919
e-ISBN	9781467312288
e-ISBN	9781467312271
DOI	10.1109/CVPR.2012.6247716
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Grammar Shape Layout Buildings Semantics Evolutionary computation Solid modeling
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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