{"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/bit-planes-dense-subpixel-alignment-of-binary","title":"Bit-Planes: Dense Subpixel Alignment of Binary Descriptors","arxiv_id":"1602.00307","date":"2016-01-31","proceeding":null,"authors":["Hatem Alismail","Brett Browning","Simon Lucey"],"abstract":"Binary descriptors have been instrumental in the recent evolution of\ncomputationally efficient sparse image alignment algorithms. Increasingly,\nhowever, the vision community is interested in dense image alignment methods,\nwhich are more suitable for estimating correspondences from high frame rate\ncameras as they do not rely on exhaustive search. However, classic dense\nalignment approaches are sensitive to illumination change. In this paper, we\npropose an easy to implement and low complexity dense binary descriptor, which\nwe refer to as bit-planes, that can be seamlessly integrated within a\nmulti-channel Lucas & Kanade framework. This novel approach combines the\nrobustness of binary descriptors with the speed and accuracy of dense alignment\nmethods. The approach is demonstrated on a template tracking problem achieving\nstate-of-the-art robustness and faster than real-time performance on consumer\nlaptops (400+ fps on a single core Intel i7) and hand-held mobile devices (100+\nfps on an iPad Air 2).","url_abs":"http://arxiv.org/abs/1602.00307v1","url_pdf":"http://arxiv.org/pdf/1602.00307v1.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":"bit-planes-dense-subpixel-alignment-of-binary","repo_url":"https://github.com/wccdyp/bpvo","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}