{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T15:42:47Z","timestamp":1777650167979,"version":"3.51.4"},"reference-count":36,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61773219"],"award-info":[{"award-number":["61773219"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2020,1]]},"abstract":"<jats:p> This paper proposes a simultaneous localization and mapping (SLAM)-based markerless mobile-end tracking registration algorithm to address the problem of virtual image drift caused by fast camera motion in mobile-augmented reality (AR). The proposed algorithm combines the AGAST-FREAK-SLAM algorithm with inertial measurement unit (IMU) data to construct a scene map and localize the camera\u2019s pose. The extracted feature points are matched with feature points in a map library for real-time camera localization and precise registration of virtual objects. Experimental results show that the proposed method can track feature points in real time, accurately construct scene maps, and locate cameras; moreover, it improves upon the tracking and registration robustness of earlier algorithms. <\/jats:p>","DOI":"10.1142\/s0218001420540051","type":"journal-article","created":{"date-parts":[[2019,3,20]],"date-time":"2019-03-20T04:25:55Z","timestamp":1553055955000},"page":"2054005","source":"Crossref","is-referenced-by-count":21,"title":["A SLAM-Based Mobile Augmented Reality Tracking Registration Algorithm"],"prefix":"10.1142","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4900-6588","authenticated-orcid":false,"given":"Jia","family":"Liu","sequence":"first","affiliation":[{"name":"B-DAT & CICAEET, School of Automation, Nanjing University of Information Science & Technology, Nanjing 210044, P. R. 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