4957

Adaptive, real-time visual simultaneous localization and mapping

Brian Clipp, Christopher Zach, Jongwoo Lim, Jan-Michael Frahm, Marc Pollefeys
Department of Computer Science, The University of North Carolina, Chapel Hill, NC, USA
Workshop on Applications of Computer Vision (WACV), 2009

@inproceedings{clipp2009adaptive,

   title={Adaptive, real-time visual simultaneous localization and mapping},

   author={Clipp, B. and Zach, C. and Lim, J. and Frahm, J.M. and Pollefeys, M.},

   booktitle={Applications of Computer Vision (WACV), 2009 Workshop on},

   pages={1–8},

   year={2009},

   organization={IEEE}

}

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In this paper we present a real-time simultaneous localization and mapping system which uses a stereo camera as its only input. We combine the benefits of KLT feature tracking, which include high speed and robustness to repetitive features, with wide baseline features, which allow for feature matching after large camera motions. Updating the map of feature locations and camera poses is considerably more expensive than performing KLT tracking. For this reason we use the optical flow measured by the KLT tracker to adaptively select key frames for which we do a full map and camera pose update. In this way we limit the processing to only
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