High resolution surface reconstruction from overlapping multiple-views

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High resolution surface reconstruction from overlapping multiple-views

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Annual Symposium on Computational Geometry archive
Proceedings of the 25th annual symposium on Computational geometry table of contents

Aarhus, Denmark

SESSION: Video and multimedia presentations table of contents

Pages: 104-105

Year of Publication: 2009

ISBN:978-1-60558-501-7

Authors

Nader Salman	INRIA, Sophia Antipolis, France
Mariette Yvinec	INRIA, Sophia Antipolis, France

Sponsors

ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

Publisher

ACM New York, NY, USA

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ABSTRACT

Extracting a computer model of a real scene from a sequence of views, is one of the most challenging and fundamental problems in computer vision. Stereo vision algorithms allow us to extract from the images a sparse 3D point cloud on the scene surfaces. However, computing an accurate mesh of the scene based on such poor quality data points (noise, sparsity) is very difficult. Here we describe a simple yet original approach that uses both the stereo vision extracted point cloud and the calibrated images. Our method is a three-stage process in which the first stage merges, filters and smoothes the input 3D points. The second stage builds for each calibrated image a triangular depth-map and fuses the set of depth-maps into a triangle soup that minimize violations of size and visibility constraints. Finally, a mesh is computed from the triangle soup using a reconstruction method that combines restricted Delaunay triangulation and Delaunay refinement.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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