{"id":19580208,"url":"https://github.com/xclud/rust-umeyama","last_synced_at":"2026-05-12T23:34:15.928Z","repository":{"id":224477233,"uuid":"763376216","full_name":"xclud/rust-umeyama","owner":"xclud","description":"An algorithm for finding the optimal translation, rotation, and scaling that aligns two sets of points with minimum root-mean-square deviation (RMSD).","archived":false,"fork":false,"pushed_at":"2024-02-26T07:20:40.000Z","size":3,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-04-29T19:44:08.704Z","etag":null,"topics":["data-science","machine-learning","machine-learning-algorithms","point-set-registration","umeyama"],"latest_commit_sha":null,"homepage":"https://docs.rs/crate/umeyama","language":"Rust","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/xclud.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2024-02-26T07:14:29.000Z","updated_at":"2024-04-29T19:44:08.705Z","dependencies_parsed_at":"2024-02-26T07:42:50.021Z","dependency_job_id":null,"html_url":"https://github.com/xclud/rust-umeyama","commit_stats":null,"previous_names":["xclud/rust-umeyama"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xclud%2Frust-umeyama","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xclud%2Frust-umeyama/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xclud%2Frust-umeyama/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xclud%2Frust-umeyama/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/xclud","download_url":"https://codeload.github.com/xclud/rust-umeyama/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240849053,"owners_count":19867617,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","machine-learning","machine-learning-algorithms","point-set-registration","umeyama"],"created_at":"2024-11-11T07:24:08.477Z","updated_at":"2025-11-10T01:03:37.276Z","avatar_url":"https://github.com/xclud.png","language":"Rust","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Umeyama\n\nThe Kabsch-Umeyama algorithm is a method for finding the optimal translation, rotation, and scaling that aligns two sets of points with minimum root-mean-square deviation (RMSD). It is named after Wolfgang Kabsch and Shinji Umeyama, who independently developed the algorithm for different applications. It is useful for comparing molecular and protein structures, point-set registration, and physics simulation.\n\nSome of the main steps of the algorithm are:\n\n* Calculate the centroids of the two sets of points and translate them to the origin.\n* Compute the covariance matrix of the translated points and perform singular value decomposition on it.\n* Determine the optimal rotation matrix and scale factor using the singular values and the sign of the determinant of the orthogonal matrices.\n* Apply the translation, rotation, and scaling to the second set of points to align it with the first set.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxclud%2Frust-umeyama","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxclud%2Frust-umeyama","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxclud%2Frust-umeyama/lists"}