{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/high-dynamic-range-slam-with-map-aware","title":"High Dynamic Range SLAM with Map-Aware Exposure Time Control","arxiv_id":"1804.07427","date":"2018-04-20","proceeding":null,"authors":["Sergey V. Alexandrov","Johann Prankl","Michael Zillich","Markus Vincze"],"abstract":"The research in dense online 3D mapping is mostly focused on the geometrical\naccuracy and spatial extent of the reconstructions. Their color appearance is\noften neglected, leading to inconsistent colors and noticeable artifacts. We\nrectify this by extending a state-of-the-art SLAM system to accumulate colors\nin HDR space. We replace the simplistic pixel intensity averaging scheme with\nHDR color fusion rules tailored to the incremental nature of SLAM and a noise\nmodel suitable for off-the-shelf RGB-D cameras. Our main contribution is a\nmap-aware exposure time controller. It makes decisions based on the global\nstate of the map and predicted camera motion, attempting to maximize the\ninformation gain of each observation. We report a set of experiments\ndemonstrating the improved texture quality and advantages of using the custom\ncontroller that is tightly integrated in the mapping loop.","url_abs":"http://arxiv.org/abs/1804.07427v1","url_pdf":"http://arxiv.org/pdf/1804.07427v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"high-dynamic-range-slam-with-map-aware","repo_url":"https://github.com/taketwo/ElasticFusion","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}