Large-­scale 3D Modeling from Crowdsourced Data

Description / Schedule / Organizers / Links / References

Description

Large-scale image-based 3D modeling has been a major goal of computer vision, enabling a wide range of applications including virtual reality, image-based localization, and autonomous navigation. One of the most diverse data sources for modeling is Internet photo collections. In the last decade, the computer vision community has made tremendous progress in large-scale structure-from-motion and multi-view stereo from Internet datasets. However, utilizing this wealth of information for 3D modeling remains a challenging problem due to the ever-increasing amount of image data. In a short period of time, research in large-scale modeling has progressed from modeling using several thousand images, to modeling from city-scale datasets of several million, and recently to reconstructing an Internet-scale dataset comprising 100 million images. This tutorial will present the main underlying technologies enabling these innovations.

Schedule (July 21, 2017 9:00-17:30)

Organizers

Jan-Michael Frahm
jmf (at) cs.unc.edu
Associate Professor, UNC Chapel Hill

Enrique Dunn
edunn (at) stevens.edu
Associate Professor, Stevens Institute of Technology

Marc Pollefeys
marc.pollefeys (at) inf.ethz.ch
Full Professor, ETH Zürich
Director of Science, Microsoft HoloLens

Jared Heinly
jared.heinly (at) urcventures.com
Senior Research Engineer, URC Ventures

Johannes L. Schönberger
jsch (at) inf.ethz.ch
Ph.D. Student, ETH Zürich

References