Sorting unorganized photo sets for urban reconstruction

Guowei Wan*, Noah Snavely, Daniel Cohen-Or, Qian Zheng, Baoquan Chen, Sikun Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In spite of advanced acquisition technology, consumer cameras remain an attractive means for capturing 3D data. For reconstructing buildings it is easy to obtain large numbers of photos representing complete, all-around coverage of a building; however, such large photos collections are often unordered and unorganized, with unknown viewpoints. We present a method for reconstructing piecewise planar building models based on a near-linear time process that sorts such unorganized collections, quickly creating an image graph, an initial pose for each camera, and a piecewise-planar facade model. Our sorting technique first estimates single-view, piecewise planar geometry from each photo, then merges these single-view models together in an analysis phase that reasons about the global scene geometry. A key contribution of our technique is to perform this reasoning based on a number of typical constraints of buildings. This sorting process results in a piecewise planar model of the scene, a set of good initial camera poses, and a correspondence between photos. This information is useful in itself as an approximate scene model, but also represents a good initialization for structure from motion and multi-view stereo techniques from which refined models can be derived, at greatly reduced computational cost compared to prior techniques.

Original languageEnglish
Pages (from-to)14-28
Number of pages15
JournalGraphical Models
Volume74
Issue number1
DOIs
StatePublished - Jan 2012

Keywords

  • Multi-view stereo
  • Photo analysis
  • Structure-from-motion
  • Urban modeling

Fingerprint

Dive into the research topics of 'Sorting unorganized photo sets for urban reconstruction'. Together they form a unique fingerprint.

Cite this