4.6 Article

Direct Visual Odometry in Low Light Using Binary Descriptors

Journal

IEEE ROBOTICS AND AUTOMATION LETTERS
Volume 2, Issue 2, Pages 444-451

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2016.2635686

Keywords

Low light vision; mapping; robust visual odometry; SLAM; visual tracking

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Feature descriptors are powerful tools for photometrically and geometrically invariant image matching. To date, however, their use has been tied to sparse interest point detection, which is susceptible to noise under adverse imaging conditions. In this letter, we propose to use binary feature descriptors in a direct tracking framework without relying on sparse interest points. This novel combination of feature descriptors and direct tracking is shown to achieve robust and efficient visual odometry with applications to poorly lit subterranean environments.

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