Department of Electrical Engineering (ISY)

Rolling Shutter Bundle Adjustment

Johan Hedborg, Per-Erik Forssén, Michael Felsberg, Erik Ringaby
CVPR12, Providence, Rhode Island, USA
IEEE Conference on Computer Vision and Pattern Recognition
June 2012

Abstract

This paper introduces a bundle adjustment (BA) method that obtains accurate structure and motion from rolling shutter (RS) video sequences: RSBA. When a classical BA algorithm processes a rolling shutter video, the resultant camera trajectory is brittle, and complete failures are not uncommon. We exploit the temporal continuity of the camera motion to define residuals of image point trajectories with respect to the camera trajectory. We compare the camera trajectories from RSBA to those from classical BA, and from classical BA on rectified videos. The comparisons are done on real video sequences from an iPhone 4, with ground truth obtained from a global shutter camera, rigidly mounted to the iPhone 4. Compared to classical BA, the rolling shutter model requires just six extra parameters. It also degrades the sparsity of the system Jacobian slightly, but as we demonstrate, the increase in computation time is moderate. Decisive advantages are that RSBA succeeds in cases where competing methods diverge, and consistently produces more accurate results.

Full Paper

Portable document format file PDF ()
Supplemental material PDF.
A4 version of poster PDF.
The dataset introduced in the paper is available here.

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Bibtex entry

@InProceedings{hedborg12,
  author = 	 {Johan Hedborg and Per-Erik Forss\'en and Michael Felsberg and Erik Ringaby},
  title = 	 {Rolling Shutter Bundle Adjustment},
  booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition},
  year = 	 {2012},
  address = 	 {Providence, Rhode Island, USA},
  month = 	 {June},
  organization = {{IEEE}},
  publisher = {{IEEE} Computer Society},
  isbn = {978-1-4673-1227-1},
  note = {http://dx.doi.org/10.1109/CVPR.2012.6247831}
}