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Towards Long Term SLAM on Thermal Imagery
April 1, 2024, 4:44 a.m. | Colin Keil, Aniket Gupta, Pushyami Kaveti, Hanumant Singh
cs.CV updates on arXiv.org arxiv.org
Abstract: Visual SLAM with thermal imagery, and other low contrast visually degraded environments such as underwater, or in areas dominated by snow and ice, remain a difficult problem for many state of the art (SOTA) algorithms. In addition to challenging front-end data association, thermal imagery presents an additional difficulty for long term relocalization and map reuse. The relative temperatures of objects in thermal imagery change dramatically from day to night. Feature descriptors typically used for relocalization …
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