Joint feature tracking and radiometric calibration from auto-exposure video

Seon Joo Kim, Jan Michael Frahm, Marc Pollefeys

Research output: Contribution to conferencePaper

12 Citations (Scopus)

Abstract

To capture the full brightness range of natural scenes, cameras automatically adjust the exposure value which causes the brightness of scene points to change from frame to frame. Given such a video sequence, we introduce a new method for tracking features and estimating the radiometric response function of the camera and the exposure difference between frames simultaneously. We model the global and nonlinear process that is responsible for the changes in image brightness rather than adapting to the changes locally and linearly which makes our tracking more robust to the change in brightness. The radiometric response function and the exposure difference between frames are also estimated in the process which enables further video processing algorithms to deal with the varying brightness.

Original languageEnglish
DOIs
Publication statusPublished - 2007 Dec 1
Event2007 IEEE 11th International Conference on Computer Vision, ICCV - Rio de Janeiro, Brazil
Duration: 2007 Oct 142007 Oct 21

Other

Other2007 IEEE 11th International Conference on Computer Vision, ICCV
CountryBrazil
CityRio de Janeiro
Period07/10/1407/10/21

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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    Kim, S. J., Frahm, J. M., & Pollefeys, M. (2007). Joint feature tracking and radiometric calibration from auto-exposure video. Paper presented at 2007 IEEE 11th International Conference on Computer Vision, ICCV, Rio de Janeiro, Brazil. https://doi.org/10.1109/ICCV.2007.4408945