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Robustness to lighting variations: An RGB-D indoor visual odometry using line segments
2015
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Large lighting variation challenges all visual odometry methods, even with RGB-D cameras. Here we propose a line segment-based RGB-D indoor odometry algorithm robust to lighting variation. We know line segments are abundant indoors and less sensitive to lighting change than point features. However, depth data are often noisy, corrupted or even missing for line segments which are often found on object boundaries where significant depth discontinuities occur. Our algorithm samples depth data
doi:10.1109/iros.2015.7353447
dblp:conf/iros/LuS15
fatcat:wbtwgmbeajdgvp4jgeowgwwh4q