Paper in IEEE ICCP 2012: “Calibration-Free Rolling Shutter Removal”

Calibration-Free Rolling Shutter Removal

• M. Grundmann, V. Kwatra, Daniel Castro, and I. Essa (2012), “Calibration-Free Rolling Shutter Removal,” in IEEE Conference on Computational Photography (ICCP), 2012. (Best Paper Award) [PDF] [WEBSITE] [VIDEO] [DOI] [BIBTEX]

  @InProceedings{ 2012-Grundmann-CRSR,
  author  = {Matthias Grundmann and Vivek Kwatra and Daniel
  Castro and Irfan Essa},
  awards  = {(Best Paper Award)},
  booktitle  = {{IEEE Conference on Computational Photography
  (ICCP)}},
  doi = {10.1109/ICCPhot.2012.6215213},
  pdf = {http://www.cc.gatech.edu/~irfan/p/2012-Grundmann-CRSR.pdf},
  publisher  = {IEEE Computer Society},
  title = {Calibration-Free Rolling Shutter Removal},
  url = {http://www.cc.gatech.edu/cpl/projects/rollingshutter/},
  video = {http://www.youtube.com/watch?v=_Pr_fpbAok8},
  year = {2012}
  }

Abstract

We present a novel algorithm for efficient removal of rolling shutter distortions in uncalibrated streaming videos. Our proposed method is calibration-free as it does not need any knowledge of the camera used, nor does it require calibration using specially recorded calibration sequences. Our algorithm can perform rolling shutter removal under varying focal lengths, as in videos from CMOS cameras equipped with an optical zoom. We evaluate our approach across a broad range of cameras and video sequences demonstrating robustness, scalability, and repeatability. We also conducted a user study, which demonstrates a preference for the output of our algorithm over other state-of-the-art methods. Our algorithm is computationally efficient, easy to parallelize, and robust to challenging artifacts introduced by various cameras with differing technologies.
Presented at IEEE International Conference on Computational Photography, Seattle, WA, April 27-29, 2012.
Winner of BEST PAPER AWARD.