{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T22:26:12Z","timestamp":1766269572933,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,7,25]],"date-time":"2018-07-25T00:00:00Z","timestamp":1532476800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Recently, monocular localization has attracted increased attention due to its application to indoor navigation and augmented reality. In this paper, a drift-aware monocular localization system that performs global and local localization is presented based on a pre-constructed dense three-dimensional (3D) map. In global localization, a pixel-distance weighted least squares algorithm is investigated for calculating the absolute scale for the epipolar constraint. To reduce the accumulative errors that are caused by the relative position estimation, a map interaction-based drift detection method is introduced in local localization, and the drift distance is computed by the proposed line model-based maximum likelihood estimation sample consensus (MLESAC) algorithm. The line model contains a fitted line segment and some visual feature points, which are used to seek inliers of the estimated feature points for drift detection. Taking advantage of the drift detection method, the monocular localization system switches between the global and local localization modes, which effectively keeps the position errors within an expected range. The performance of the proposed monocular localization system is evaluated on typical indoor scenes, and experimental results show that compared with the existing localization methods, the accuracy improvement rates of the absolute position estimation and the relative position estimation are at least 30.09% and 65.59%, respectively.<\/jats:p>","DOI":"10.3390\/ijgi7080299","type":"journal-article","created":{"date-parts":[[2018,7,25]],"date-time":"2018-07-25T08:28:47Z","timestamp":1532507327000},"page":"299","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Drift-Aware Monocular Localization Based on a Pre-Constructed Dense 3D Map in Indoor Environments"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8282-2793","authenticated-orcid":false,"given":"Guanyuan","family":"Feng","sequence":"first","affiliation":[{"name":"School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1684-9714","authenticated-orcid":false,"given":"Lin","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuezhi","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5829-6121","authenticated-orcid":false,"given":"Danyang","family":"Qin","sequence":"additional","affiliation":[{"name":"Electronic Engineering College, Heilongjiang University, Harbin 150080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1002\/wics.158","article-title":"Global navigation satellite systems","volume":"3","author":"Grewal","year":"2011","journal-title":"Wiley Interdiscip. Rev. Comput. Stat."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"8328","DOI":"10.1038\/srep08328","article-title":"Precise positioning with current multi-constellation global navigation satellite systems: GPS, GLONASS, Galileo and BeiDou","volume":"5","author":"Li","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1109\/MCOM.2015.7060497","article-title":"WiFi-based indoor positioning","volume":"53","author":"Yang","year":"2015","journal-title":"IEEE Commun. Mag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.1109\/JSYST.2016.2525814","article-title":"A map-assisted WiFi AP placement algorithm enabling mobile device\u2019s indoor positioning","volume":"11","author":"Du","year":"2017","journal-title":"IEEE Syst. J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"728","DOI":"10.1109\/TIM.2014.2347691","article-title":"Real-time RFID indoor positioning system based on Kalman-filter drift removal and Heron-bilateration location estimation","volume":"64","author":"Huang","year":"2015","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Wang, C., Shi, Z., and Wu, F. (2017). Intelligent RFID indoor localization system using a gaussian filtering based extreme learning machine. Symmetry, 9.","DOI":"10.3390\/sym9030030"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2272","DOI":"10.1109\/TITS.2016.2516822","article-title":"Positioning techniques in indoor environments based on stochastic modeling of UWB round-trip-time measurements","volume":"17","author":"De","year":"2016","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1109\/TAES.2014.130722","article-title":"UWB-based localization in large indoor scenarios: Optimized placement of anchor nodes","volume":"51","author":"Monica","year":"2015","journal-title":"IEEE Aerosp. Electron. Syst. Mag."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Huitl, R., Schroth, G., Hilsenbeck, S., Schweiger, F., and Steinbach, E. (October, January 30). TUMindoor: An extensive image and point cloud dataset for visual indoor localization and mapping. Proceedings of the 2012 19th IEEE International Conference on Image Processing, Lake Buena Vista, FL, USA.","DOI":"10.1109\/ICIP.2012.6467224"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2017\/8037607","article-title":"Visual map construction using RGB-D sensors for image-based localization in indoor environments","volume":"99","author":"Feng","year":"2017","journal-title":"J. Sens."},{"key":"ref_11","unstructured":"Se, S., Lowe, D., and Little, J. (November, January 29). Local and global localization for mobile robots using visual landmarks. Proceedings of the 2001 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Maui, HI, USA."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1109\/MRA.2011.943233","article-title":"Visual odometry [tutorial]","volume":"18","author":"Scaramuzza","year":"2011","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_13","unstructured":"Choi, S., Joung, J.H., Yu, W., and Cho, J.I. (2011, January 26\u201329). What does ground tell us? Monocular visual odometry under planar motion constraint. Proceedings of the 2011 11th International Conference on Control, Automation and Systems, Gyeonggi-do, Korea."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1109\/TRO.2008.2004490","article-title":"Appearance-guided monocular omnidirectional visual odometry for outdoor ground vehicles","volume":"24","author":"Scaramuzza","year":"2008","journal-title":"IEEE Trans. Robot."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Choi, S., Park, J., and Yu, W. (November, January 30). Resolving scale ambiguity for monocular visual odometry. Proceedings of the 2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence, Jeju, Korea.","DOI":"10.1109\/URAI.2013.6677403"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sadeghi, H., Valaee, S., and Shirani, S. (2014, January 22\u201325). A weighted KNN epipolar geometry-based approach for vision-based indoor localization using smartphone cameras. Proceedings of the 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, A Coruna, Spain.","DOI":"10.1109\/SAM.2014.6882332"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Ma, L., and Tan, X. (2016, January 5\u20139). Smart phone camera image localization method for narrow corridors based on epipolar geometry. Proceedings of the 2016 International Wireless Communications and Mobile Computing Conference, Paphos, Cyprus.","DOI":"10.1109\/IWCMC.2016.7577135"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4678","DOI":"10.1109\/TVT.2016.2615630","article-title":"2DTriPnP: A robust two-dimensional method for fine visual localization using Google streetview database","volume":"66","author":"Sadeghi","year":"2016","journal-title":"IEEE Veh. Technol. Mag."},{"key":"ref_19","unstructured":"Deretey, E. (2016). Visual Localization in Underground Mines and Indoor Environments Using PnP. [Master\u2019s Thesis, Queen\u2019s University]."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Deretey, E., Ahmed, M.T., Marshall, J.A., and Greenspan, M. (2015, January 13\u201316). Visual indoor positioning with a single camera using PnP. Proceedings of the 2015 International Conference on Indoor Positioning and Indoor Navigation, Banff, AB, Canada.","DOI":"10.1109\/IPIN.2015.7346756"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Esteban, I., Dorst, L., and Dijk, J. (2010, January 10\u201312). Closed form solution for the scale ambiguity problem in monocular visual odometry. Proceedings of the International Conference on Intelligent Robotics and Applications, Shanghai, China.","DOI":"10.1007\/978-3-642-16584-9_64"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1007\/s11263-008-0152-6","article-title":"EPnP: An accurate o(n) solution to the PnP problem","volume":"81","author":"Lepetit","year":"2009","journal-title":"Int. J. Comput. Vis."},{"key":"ref_23","unstructured":"K\u00fcmmerle, R., Grisetti, G., Strasdat, H., Konolige, K., and Burgard, W. (2011, January 9\u201313). G2o: A general framework for graph optimization. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China."},{"key":"ref_24","unstructured":"Hartley, R., and Zisserman, A. (2000). Multiple View Geometry in Computer Vision, Cambridge University Press. [2nd ed.]."},{"key":"ref_25","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_26","doi-asserted-by":"crossref","first-page":"1255","DOI":"10.1109\/TRO.2017.2705103","article-title":"ORB-SLAM2: An open-source slam system for monocular, stereo, and RGB-D cameras","volume":"33","year":"2017","journal-title":"IEEE Trans. Robot."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1006\/cviu.1999.0832","article-title":"MLESAC: A new robust estimator with application to estimating image geometry","volume":"78","author":"Torr","year":"2000","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_28","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 IEEE International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Nowak, E., Jurie, F., and Triggs, B. (2006, January 7\u201313). Sampling strategies for bag-of-features image classification. Proceedings of the European Conference on Computer Vision 2006, Graz, Austria.","DOI":"10.1007\/11744085_38"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1615","DOI":"10.1109\/TPAMI.2005.188","article-title":"A performance evaluation of local descriptors","volume":"27","author":"Mikolajczyk","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1109\/TPAMI.2004.17","article-title":"An efficient solution to the five-point relative pose problem","volume":"26","year":"2004","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1090\/qam\/10666","article-title":"A method for the solution of certain non-linear problems in least squares","volume":"2","author":"Levenberg","year":"1944","journal-title":"Q. Appl. Math."},{"key":"ref_33","unstructured":"Strutz, T. (2011). Data Fitting and Uncertainty: A Practical Introduction to Weighted Least Squares and Beyond, Vieweg and Teubner. [1st ed.]."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1109\/34.601246","article-title":"In defense of the eight-point algorithm","volume":"19","author":"Hartley","year":"1997","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Kanatani, K., Sugaya, Y., and Niitsuma, H. (2008, January 1\u20134). Triangulation from two views revisited: Hartley-Sturm vs. optimal correction. Proceedings of the 19th British Machine Vision Conference, Leeds, UK.","DOI":"10.5244\/C.22.18"},{"key":"ref_36","unstructured":"Kanatani, K. (2005). Statistical Optimization for Geometric Computation: Theory and Practice, Courier Corporation."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1109\/TPAMI.1987.4767965","article-title":"Least-squares fitting of two 3-D point sets","volume":"5","author":"Arun","year":"1987","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Mouragnon, E., Lhuillier, M., Dhome, M., Dekeyser, F., and Sayd, P. (2006, January 17\u201322). Real time localization and 3D reconstruction. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, New York, NY, USA.","DOI":"10.1109\/CVPR.2006.236"},{"key":"ref_39","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_40","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1109\/34.709604","article-title":"Breakpoint detection using covariance propagation","volume":"20","author":"Ji","year":"1998","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1006\/cviu.1997.0547","article-title":"Triangulation","volume":"68","author":"Hartley","year":"1997","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1109\/TRO.2008.2004637","article-title":"Large-scale 6-DOF SLAM with stereo-in-hand","volume":"24","author":"Paz","year":"2008","journal-title":"IEEE Trans. Robot."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.3390\/s120201437","article-title":"Accuracy and resolution of kinect depth data for indoor mapping applications","volume":"12","author":"Khoshelham","year":"2012","journal-title":"Sensors"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2058","DOI":"10.1109\/TPAMI.2012.125","article-title":"Joint depth and color camera calibration with distortion correction","volume":"34","author":"Herrera","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/7\/8\/299\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:14:21Z","timestamp":1760195661000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/7\/8\/299"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,25]]},"references-count":44,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["ijgi7080299"],"URL":"https:\/\/doi.org\/10.3390\/ijgi7080299","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2018,7,25]]}}}