{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:23:04Z","timestamp":1754155384013,"version":"3.41.2"},"reference-count":39,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2018,10,16]],"date-time":"2018-10-16T00:00:00Z","timestamp":1539648000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IR"],"published-print":{"date-parts":[[2018,12,7]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Typical feature-matching algorithms use only unary constraints on appearances to build correspondences where little structure information is used. Ignoring structure information makes them sensitive to various environmental perturbations. The purpose of this paper is to propose a novel graph-based method that aims to improve matching accuracy by fully exploiting the structure information.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>Instead of viewing a frame as a simple collection of keypoints, the proposed approach organizes a frame as a graph by treating each keypoint as a vertex, where structure information is integrated in edges between vertices. Subsequently, the matching process of finding keypoint correspondence is formulated in a graph matching manner.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The authors compare it with several state-of-the-art visual simultaneous localization and mapping algorithms on three datasets. Experimental results reveal that the ORB-G algorithm provides more accurate and robust trajectories in general.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>Instead of viewing a frame as a simple collection of keypoints, the proposed approach organizes a frame as a graph by treating each keypoint as a vertex, where structure information is integrated in edges between vertices. Subsequently, the matching process of finding keypoint correspondence is formulated in a graph matching manner.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ir-04-2018-0061","type":"journal-article","created":{"date-parts":[[2018,10,16]],"date-time":"2018-10-16T06:05:19Z","timestamp":1539669919000},"page":"679-687","source":"Crossref","is-referenced-by-count":4,"title":["Graph-based visual odometry for VSLAM"],"prefix":"10.1108","volume":"45","author":[{"given":"Shaoyan","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Congyan","family":"Lang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Songhe","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2018,10,16]]},"reference":[{"issue":"3","key":"key2021041507271461800_ref001","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","article-title":"Speeded-up robust features (surf)","volume":"110","year":"2008","journal-title":"Computer Vision and Image Understanding"},{"issue":"10","key":"key2021041507271461800_ref002","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1177\/0278364915620033","article-title":"The euroc micro aerial vehicle datasets","volume":"35","year":"2016","journal-title":"The International Journal of Robotics Research"},{"key":"key2021041507271461800_ref003","first-page":"903","article-title":"Visual odometry on the mars exploration rovers","volume-title":"2005 IEEE International Conference on Systems, Man and Cybernetics","year":"2005"},{"issue":"4","key":"key2021041507271461800_ref004","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1109\/34.993559","article-title":"Structure from motion causally integrated over time","volume":"24","year":"2002","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"key2021041507271461800_ref005","first-page":"492","article-title":"Reweighted random walks for graph matching","volume-title":"European conference on Computer Vision","year":"2010"},{"issue":"5","key":"key2021041507271461800_ref006","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1002\/rob.20345","article-title":"1-point ransac for extended kalman filtering: application to real-time structure from motion and visual odometry","volume":"27","year":"2010","journal-title":"Journal of Field Robotics"},{"issue":"6","key":"key2021041507271461800_ref007","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.1109\/TPAMI.2007.1049","article-title":"Monoslam: real-time single camera slam","volume":"29","year":"2007","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"key2021041507271461800_ref008","first-page":"834","article-title":"Lsd-slam: large-scale direct monocular slam","volume-title":"European Conference on Computer Vision","year":"2014"},{"first-page":"1","article-title":"Real-time 3D visual slam with a hand-held rgb-d camera","year":"2011","key":"key2021041507271461800_ref009"},{"first-page":"25","article-title":"Motion and structure from point and line matches","year":"1987","key":"key2021041507271461800_ref010"},{"issue":"11","key":"key2021041507271461800_ref011","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1177\/0278364913491297","article-title":"Vision meets robotics: the kitti dataset","volume":"32","year":"2013","journal-title":"The International Journal of Robotics Research"},{"key":"key2021041507271461800_ref012","first-page":"02175","article-title":"Keyframe-based visual-inertial online slam with relocalization","volume":"1702","year":"2017","journal-title":"arXiv Preprint arXiv"},{"key":"key2021041507271461800_ref013","first-page":"2100","article-title":"Dense visual slam for rgb-d cameras","volume-title":"2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","year":"2013"},{"key":"key2021041507271461800_ref014","first-page":"225","article-title":"Parallel tracking and mapping for small ar workspaces","volume-title":"6th IEEE and ACM International Symposium on Mixed and Augmented Reality, 2007. 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