{"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/gms-grid-based-motion-statistics-for-fast","title":"GMS: Grid-based Motion Statistics for Fast, Ultra-Robust Feature Correspondence","arxiv_id":null,"date":"2017-07-01","proceeding":"CVPR 2017 7","authors":["Jia-Wang Bian","Wen-Yan Lin","Yasuyuki Matsushita","Sai-Kit Yeung","Tan-Dat Nguyen","Ming-Ming Cheng"],"abstract":"Incorporating smoothness constraints into feature matching is known to enable ultra-robust matching. However, such formulations are both complex and slow, making them unsuitable for video applications. This paper proposes GMS (Grid-based Motion Statistics), a simple means of encapsulating motion smoothness as the statistical likelihood of a certain number of matches in a region. GMS enables translation of high match numbers into high match quality. This provides a real-time, ultra-robust correspondence system. Evaluation on videos, with low textures, blurs and wide-baselines show GMS consistently out-performs other real-time matchers and can achieve parity with more sophisticated, much slower techniques.\r","url_abs":"http://openaccess.thecvf.com/content_cvpr_2017/html/Bian_GMS_Grid-based_Motion_CVPR_2017_paper.html","url_pdf":"http://openaccess.thecvf.com/content_cvpr_2017/papers/Bian_GMS_Grid-based_Motion_CVPR_2017_paper.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":"gms-grid-based-motion-statistics-for-fast","repo_url":"https://github.com/JiawangBian/GMS-Feature-Matcher","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}