{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T05:53:15Z","timestamp":1780379595386,"version":"3.54.1"},"reference-count":41,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2017,5,5]],"date-time":"2017-05-05T00:00:00Z","timestamp":1493942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51175026"],"award-info":[{"award-number":["51175026"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Defence Industrial Technology Development Program","award":["JCKY2016601C004"],"award-info":[{"award-number":["JCKY2016601C004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In mobile augmented\/virtual reality (AR\/VR), real-time 6-Degree of Freedom (DoF) motion tracking is essential for the registration between virtual scenes and the real world. However, due to the limited computational capacity of mobile terminals today, the latency between consecutive arriving poses would damage the user experience in mobile AR\/VR. Thus, a visual-inertial based real-time motion tracking for mobile AR\/VR is proposed in this paper. By means of high frequency and passive outputs from the inertial sensor, the real-time performance of arriving poses for mobile AR\/VR is achieved. In addition, to alleviate the jitter phenomenon during the visual-inertial fusion, an adaptive filter framework is established to cope with different motion situations automatically, enabling the real-time 6-DoF motion tracking by balancing the jitter and latency. Besides, the robustness of the traditional visual-only based motion tracking is enhanced, giving rise to a better mobile AR\/VR performance when motion blur is encountered. Finally, experiments are carried out to demonstrate the proposed method, and the results show that this work is capable of providing a smooth and robust 6-DoF motion tracking for mobile AR\/VR in real-time.<\/jats:p>","DOI":"10.3390\/s17051037","type":"journal-article","created":{"date-parts":[[2017,5,5]],"date-time":"2017-05-05T10:31:08Z","timestamp":1493980268000},"page":"1037","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":64,"title":["Real-Time Motion Tracking for Mobile Augmented\/Virtual Reality Using Adaptive Visual-Inertial Fusion"],"prefix":"10.3390","volume":"17","author":[{"given":"Wei","family":"Fang","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering and Automation, Beihang University, Xueyuan Road, Haidian District, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lianyu","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering and Automation, Beihang University, Xueyuan Road, Haidian District, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanjun","family":"Deng","sequence":"additional","affiliation":[{"name":"Beijing Baofengmojing Technologies Co., Ltd., Zhichun Road, Haidian District, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongbo","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering and Automation, Beihang University, Xueyuan Road, Haidian District, Beijing 100191, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,5,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2633","DOI":"10.1109\/TVCG.2015.2513408","article-title":"Pose estimation for augmented reality: A hands-on survey","volume":"22","author":"Marchand","year":"2016","journal-title":"IEEE Trans. Visual. Comput. Graph."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"31092","DOI":"10.3390\/s151229847","article-title":"Sensor-aware recognition and tracking for wide-area augmented reality on mobile phones","volume":"15","author":"Chen","year":"2015","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6017","DOI":"10.3390\/s100606017","article-title":"Fast scene recognition and camera relocalisation for wide area augmented reality systems","volume":"10","author":"Guan","year":"2010","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1630","DOI":"10.1109\/TVCG.2015.2443783","article-title":"Head tracking latency in virtual environments revisited: Do users with multiple sclerosis notice latency less?","volume":"22","author":"Samaraweera","year":"2016","journal-title":"IEEE Trans. Visual. Comput. Graph."},{"key":"ref_5","first-page":"1","article-title":"A survey of tracking technology for virtual environments","volume":"8","author":"Rolland","year":"2001","journal-title":"Fundam. Wearable Comput. Augment. Real."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gerstweiler, G., Vonach, E., and Kaufmann, H. (2016). HyMoTrack: A mobile AR navigation system for complex indoor environments. Sensors, 16.","DOI":"10.3390\/s16010017"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mihelj, M., Novak, D., and Begus, S. (2014). Virtual Reality Technology and Applications, Springer.","DOI":"10.1007\/978-94-007-6910-6"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.compind.2010.07.003","article-title":"Tangible authoring of 3D virtual scenes in dynamic augmented reality environment","volume":"62","author":"Lee","year":"2011","journal-title":"Comput. Ind."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"17212","DOI":"10.3390\/s140917212","article-title":"Smart multi-level tool for remote patient monitoring based on a wireless sensor network and mobile augmented reality","volume":"14","author":"Gonzalez","year":"2014","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Tayara, H., Ham, W., and Chong, K.T. (2016). A real-time marker-based visual sensor based on a FPGA and a soft core processor. Sensors, 16.","DOI":"10.3390\/s16122139"},{"key":"ref_11","unstructured":"Pressigout, M., and Marchand, E. (2006, January 15\u201319). Real-time 3D model-based tracking: combining edge and texture information. Proceedings of the IEEE International Conference on Robotics and Automation, Orlando, FL, USA."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/j.compind.2013.01.002","article-title":"A model-based approach for data integration to improve maintenance management by mixed reality","volume":"64","author":"Espindola","year":"2013","journal-title":"Comput. Ind."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.cag.2015.05.021","article-title":"CAD-based 3D objects recognition in monocular images for mobile augmented reality","volume":"50","author":"Han","year":"2015","journal-title":"Comput. Gr."},{"key":"ref_14","unstructured":"Alex, U., and Mark, F. (2013, January 28\u201331). A markerless augmented reality system for mobile devices. Proceedings of the International Conference on Computer and Robot Vision, Regina, SK, Canada."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"8501","DOI":"10.3390\/s130708501","article-title":"A robust approach for a filter-based monocular simultaneous localization and mapping (SLAM) system","volume":"13","author":"Munguia","year":"2013","journal-title":"Sensors"},{"key":"ref_16","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 IEEE\/ACM International Symposium on Mixed and Augmented Reality, Nara, Japan.","DOI":"10.1109\/ISMAR.2007.4538852"},{"key":"ref_17","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_18","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1109\/TRO.2008.2004829","article-title":"An efficient direct approach to visual SLAM","volume":"24","author":"Silveira","year":"2008","journal-title":"IEEE Trans. Robot."},{"key":"ref_19","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 IEEE International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126513"},{"key":"ref_20","unstructured":"Jakob, E., Thomas, S., and Daniel, C. (2014, January 6\u201312). LSD-SLAM: Large-scale direct monocular SLAM. Proceedings of the European Conference on Computer Vision, Zurich, Switzerland."},{"key":"ref_21","unstructured":"Forster, C., Pizzoli, M., and Scaramuzza, D. (June, January 31). SVO: Fast semi-direct monocular visual odometry. Proceedings of the IEEE International Conference on Robotics and Automation, Hong Kong, China."},{"key":"ref_22","unstructured":"Engel, J., Koltun, V., and Cremers, D. (arXiv, 2016). Direct Sparse Odometry, arXiv."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Newcombe, R.A., and Davison, A.J. (2010, January 13\u201318). Live dense reconstruction with a single moving camera. Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5539794"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1016\/j.imavis.2007.08.015","article-title":"Real-time camera tracking for marker-less and unprepared augmented reality environments","volume":"26","author":"Xu","year":"2008","journal-title":"Image Vis. Comput."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lee, S.H., Lee, S.K., and Choi, J.S. (2009, January 25\u201328). Real-time camera tracking using a particle filter and multiple feature trackers. Proceedings of the IEEE Consumer Electronics Society\u2019s Games Innovations Conference, London, UK.","DOI":"10.1109\/ICEGIC.2009.5293577"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1007\/s00530-014-0364-2","article-title":"Wide area localization and tracking on camera phones for mobile augmented reality systems","volume":"21","author":"Wei","year":"2015","journal-title":"Multimedia Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.jvcir.2015.06.016","article-title":"An improved augmented reality system based on AndAR","volume":"37","author":"Chen","year":"2015","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_28","first-page":"1","article-title":"Real-time camera tracking using hybrid features in mobile augmented reality","volume":"58","author":"Wang","year":"2015","journal-title":"Sci. China Inf. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"16448","DOI":"10.3390\/s150716448","article-title":"An inertial and optical sensor fusion approach for six degree-of-freedom pose estimation","volume":"15","author":"He","year":"2015","journal-title":"Sensors"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1109\/TASE.2016.2582752","article-title":"Visual-inertial navigation systems for aerial robotics: Sensor fusion and technology","volume":"14","author":"Santoso","year":"2017","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_31","first-page":"12816","article-title":"Tightly-coupled stereo visual-inertial navigation using point and line features","volume":"14","author":"Kong","year":"2014","journal-title":"Sensors"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1177\/0278364914554813","article-title":"Keyframe-based visual\u2013inertial odometry using nonlinear optimization","volume":"34","author":"Leutenegger","year":"2015","journal-title":"Int. J. Robot. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1007\/978-3-642-14743-2_18","article-title":"Large-scale visual odometry for rough terrain","volume":"66","author":"Konolige","year":"2010","journal-title":"Springer Tracts Adv. Rob."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Weiss, S., and Siegwart, R. (2011, January 9\u201313). Real-time metric state estimation for modular vision-inertial systems. Proceedings of the IEEE International Conference on Robotics and Automation, Shanghai, China.","DOI":"10.1109\/ICRA.2011.5979982"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.compind.2015.05.003","article-title":"Fusion of visual odometry and inertial navigation system on a smartphone","volume":"74","author":"Tomazic","year":"2015","journal-title":"Comput. Ind."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Kim, Y., and Hwang, D.H. (2016). Vision\/INS integrated navigation system for poor vision navigation environments. Sensors, 16.","DOI":"10.3390\/s16101672"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.inffus.2016.04.006","article-title":"A novel system for object pose estimation using fused vision and inertial data","volume":"33","author":"Li","year":"2016","journal-title":"Inform. Fusion"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1109\/34.888718","article-title":"A flexible new technique for camera calibration","volume":"22","author":"Zhang","year":"2000","journal-title":"IEEE Trans. Pattern. Anal."},{"key":"ref_39","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 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan.","DOI":"10.1109\/IROS.2013.6696514"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Fang, W., Zheng, L., and Deng, H. (2016, January 11\u201313). A motion tracking method by combining the IMU and camera in mobile devices. Proceedings of the 10th International Conference on Sensing Technology, Nanjing, China.","DOI":"10.1109\/ICSensT.2016.7796235"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/70.127239","article-title":"Quaternion kinematic and dynamic differential equations","volume":"8","author":"Chou","year":"1992","journal-title":"IEEE Trans. Robot. Autom."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/5\/1037\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:34:46Z","timestamp":1760207686000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/5\/1037"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,5]]},"references-count":41,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2017,5]]}},"alternative-id":["s17051037"],"URL":"https:\/\/doi.org\/10.3390\/s17051037","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,5]]}}}