Hybrid multi-view reconstruction by jump-diffusion

Florent Lafarge, Renaud Keriven, Mathieu Brédif, Vu Hoang Hiep

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We propose a multi-view stereo reconstruction algorithm which recovers urban scenes as a combination of meshes and geometric primitives. It provides a compact model while preserving details: irregular elements such as statues and ornaments are described by meshes whereas regular structures such as columns and walls are described by primitives (planes, spheres, cylinders, cones and tori). A Jump-Diffusion process is designed to sample these two types of elements simultaneously. The quality of a reconstruction is measured by a multi-object energy model which takes into account both photo-consistency and semantic considerations (i.e. geometry and shape layout). The sampler is embedded into an iterative refinement procedure which provides an increasingly accurate hybrid representation. Experimental results on complex urban structures and large scenes are presented and compared to multi-view based meshing algorithms.

Original languageEnglish
Title of host publication2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Pages350-357
Number of pages8
DOIs
Publication statusPublished - 31 Aug 2010
Externally publishedYes
Event2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 - San Francisco, CA, United States
Duration: 13 Jun 201018 Jun 2010

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Conference

Conference2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Country/TerritoryUnited States
CitySan Francisco, CA
Period13/06/1018/06/10

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