{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T12:25:47Z","timestamp":1765887947335,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2017,11,7]],"date-time":"2017-11-07T00:00:00Z","timestamp":1510012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual\u2013inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual\u2013inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual\u2013inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual\u2013inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.<\/jats:p>","DOI":"10.3390\/s17112567","type":"journal-article","created":{"date-parts":[[2017,11,7]],"date-time":"2017-11-07T11:46:01Z","timestamp":1510055161000},"page":"2567","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Adaptive Monocular Visual\u2013Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1151-6814","authenticated-orcid":false,"given":"Jin-Chun","family":"Piao","sequence":"first","affiliation":[{"name":"Department of Computer Science, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea"}]},{"given":"Shin-Dug","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2017,11,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., and Bradski, G. (2011, January 6\u201313). Orb: An efficient alternative to sift or surf. Proceedings of the 2011 International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1109\/TRO.2015.2463671","article-title":"Orb-SLAM: A versatile and accurate monocular SLAM system","volume":"31","author":"Montiel","year":"2015","journal-title":"IEEE Trans. Robot."},{"key":"ref_3","unstructured":"Nist\u00e9r, D., Naroditsky, O., and Bergen, J. (July, January 27). Visual odometry. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Washington, DC, USA."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1109\/TRO.2008.2004514","article-title":"Fast and incremental method for loop-closure detection using bags of visual words","volume":"24","author":"Angeli","year":"2008","journal-title":"IEEE Trans. Robot."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1111\/j.2517-6161.1989.tb01764.x","article-title":"Exact maximum a posteriori estimation for binary images","volume":"51","author":"Greig","year":"1989","journal-title":"J. R. Stat. Soc. Ser. B"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.imavis.2012.02.009","article-title":"Visual SLAM: Why filter?","volume":"30","author":"Strasdat","year":"2012","journal-title":"Image Vis. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1142\/S0218001488000285","article-title":"Motion and structure from motion in a piecewise planar environment","volume":"2","author":"Faugeras","year":"1988","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Hartley, R., and Zisserman, A. (2004). Multiple View Geometry in Computer Vision, Cambridge University Press. [2nd ed.].","DOI":"10.1017\/CBO9780511811685"},{"key":"ref_9","unstructured":"Bradski, G., and Kaehler, A. (2008). Learning OpenCV: Computer Vision with the OpenCV Library, O\u2019Reilly Media, Inc."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Davison, A.J. (2003, January 13\u201316). Real-time simultaneous localisation and mapping with a single camera. Proceedings of the Ninth IEEE International Conference on Computer Vision, Nice, France.","DOI":"10.1109\/ICCV.2003.1238654"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.1109\/TPAMI.2007.1049","article-title":"Mono SLAM: Real-time single camera SLAM","volume":"29","author":"Davison","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"932","DOI":"10.1109\/TRO.2008.2003276","article-title":"Inverse depth parametrization for monocular SLAM","volume":"24","author":"Civera","year":"2008","journal-title":"IEEE Trans. Robot."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lkopf, B., and Smola, A.J. (2002). Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, MIT Press.","DOI":"10.7551\/mitpress\/4175.001.0001"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Klein, G., and Murray, D. (2007, January 13\u201316). Parallel tracking and mapping for small AR workspaces. Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality, Nara, Japan.","DOI":"10.1109\/ISMAR.2007.4538852"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Triggs, B., McLauchlan, P.F., Hartley, R.I., and Fitzgibbon, A.W. (1999). Bundle adjustment\u2014A modern synthesis. International Workshop on Vision Algorithms, Springer.","DOI":"10.1007\/3-540-44480-7_21"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mur-Artal, R., and Tard\u00f3s, D. (June, January 31). Fast relocalisation and loop closing in keyframe-based SLAM. Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China.","DOI":"10.1109\/ICRA.2014.6906953"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1109\/TRO.2012.2197158","article-title":"Bags of binary words for fast place recognition in image sequences","volume":"28","author":"Tardos","year":"2012","journal-title":"IEEE Trans. Robot."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., and Urtasun, R. (2012, January 16\u201321). Are we ready for autonomous driving? The kitti vision benchmark suite. Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, USA.","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref_19","unstructured":"Mur-Artal, R. (2017, January 19). ORB_SLAM2. Available online: https:\/\/github.com\/raulmur\/ORB_SLAM2."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Newcombe, R.A., Lovegrove, S.J., and Davison, A.J. (2011, January 6\u201313). Dtam: Dense tracking and mapping in real-time. Proceedings of the 2011 International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126513"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Engel, J., Sch\u00f6ps, T., and Cremers, D. (2014). Lsd- SLAM: Large-scale direct monocular SLAM. Computer Vision\u2014ECCV 2014, Proceedings of the 13th European Conference, Zurich, Switzerland, 6\u201312 September 2014, Springer.","DOI":"10.1007\/978-3-319-10605-2_54"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Engel, J., Koltun, V., and Cremers, D. (2017). Direct sparse odometry. IEEE Trans. Pattern Anal. Mach. Intell.","DOI":"10.1109\/TPAMI.2017.2658577"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Weiss, S., Achtelik, M.W., Lynen, S., Chli, M., and Siegwart, R. (2012, January 14\u201318). Real-time onboard visual-inertial state estimation and self-calibration of mavs in unknown environments. Proceedings of the 2012 IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA.","DOI":"10.1109\/ICRA.2012.6225147"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Fang, W., Zheng, L., Deng, H., and Zhang, H. (2017). Real-time motion tracking for mobile augmented\/virtual reality using adaptive visual-inertial fusion. Sensors, 17.","DOI":"10.3390\/s17051037"},{"key":"ref_25","unstructured":"Li, M. (2014). Visual-Inertial Odometry on Resource-Constrained Systems. [Ph.D. Thesis, University of California]."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Bloesch, M., Omari, S., Hutter, M., and Siegwart, R. (October, January 28). Robust visual inertial odometry using a direct ekf-based approach. Proceedings of the 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany.","DOI":"10.1109\/IROS.2015.7353389"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1177\/0278364914554813","article-title":"Keyframe-based Visual-Inertial odometry using nonlinear optimization","volume":"34","author":"Leutenegger","year":"2015","journal-title":"Int. J. Robot. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1109\/LRA.2017.2653359","article-title":"Visual-inertial monocular SLAM with map reuse","volume":"2","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"9623","DOI":"10.1007\/s11042-015-2999-1","article-title":"Improving performance on object recognition for real-time on mobile devices","volume":"75","author":"Piao","year":"2015","journal-title":"Multimedia Tool. Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1109\/TASE.2016.2550621","article-title":"Monocular visual-inertial state estimation with online initialization and camera-imu extrinsic calibration","volume":"14","author":"Yang","year":"2017","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Furgale, P., Rehder, J., and Siegwart, R. (2013, January 3\u20137). Unified temporal and spatial calibration for multi-sensor systems. Proceedings of the 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan.","DOI":"10.1109\/IROS.2013.6696514"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TRO.2016.2597321","article-title":"On-manifold preintegration for real-time visual-inertial odometry","volume":"33","author":"Forster","year":"2016","journal-title":"IEEE Trans. Robot."},{"key":"ref_33","unstructured":"Bertsekas, D.P. (1999). Nonlinear Programming, Athena scientific."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Mor\u00e9, J.J. (1978). The levenberg-marquardt algorithm: Implementation and theory. Numerical Analysis, Springer.","DOI":"10.1007\/BFb0067700"},{"key":"ref_35","unstructured":"K\u00fcmmerle, R., Grisetti, G., Strasdat, H., Konolige, K., and Burgard, W. (2011, January 9\u201313). G20: A general framework for graph optimization. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China."},{"key":"ref_36","unstructured":"Lucas, B.D., and Kanade, T. (1981, January 24\u201328). An iterative image registration technique with an application to stereo vision. Proceedings of the 7th International Joint Conference on Artificial Intelligence, Vancouver, BC, Canada."},{"key":"ref_37","unstructured":"Rives, P. (November, January 31). Visual servoing based on epipolar geometry. Proceedings of the 2000 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS 2000), Takamatsu, Japan."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography","volume":"24","author":"Fischler","year":"1981","journal-title":"Commun. ACM"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1007\/BF02163027","article-title":"Singular value decomposition and least squares solutions","volume":"14","author":"Golub","year":"1970","journal-title":"Numer. Math."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1177\/0278364915620033","article-title":"The euroc micro aerial vehicle datasets","volume":"35","author":"Burri","year":"2016","journal-title":"Int. J. Robot. Res."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.5194\/gmd-7-1247-2014","article-title":"Root mean square error (RMSE) or mean absolute error (MAE)?\u2014Arguments against avoiding rmse in the literature","volume":"7","author":"Chai","year":"2014","journal-title":"Geosci. Model Dev."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1364\/JOSAA.4.000629","article-title":"Closed-form solution of absolute orientation using unit quaternions","volume":"4","author":"Horn","year":"1987","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Sturm, J., Engelhard, N., Endres, F., Burgard, W., and Cremers, D. (2012, January 7\u201312). A benchmark for the evaluation of RGB-D SLAM systems. Proceedings of the 2012 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, Portugal.","DOI":"10.1109\/IROS.2012.6385773"},{"key":"ref_44","unstructured":"Bradski, G. (2017, November 07). The OpenCV Library. Available online: http:\/\/www.drdobbs.com\/open-source\/the-opencv-library\/184404319."},{"key":"ref_45","unstructured":"Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., and Ng, A.Y. (2009, January 12\u201317). ROS: An open-source robot operating system. Proceedings of the ICRA Workshop on Open Source Software, Kobe, Japan."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2567\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:48:27Z","timestamp":1760208507000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2567"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,7]]},"references-count":45,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2017,11]]}},"alternative-id":["s17112567"],"URL":"https:\/\/doi.org\/10.3390\/s17112567","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2017,11,7]]}}}