{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:40:31Z","timestamp":1772822431793,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T00:00:00Z","timestamp":1621468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"China Natural Science Foundation","award":["N2019G012, 41901412"],"award-info":[{"award-number":["N2019G012, 41901412"]}]},{"name":"National key research and development plan","award":["2019YFB2102703, 2020YFC1512001"],"award-info":[{"award-number":["2019YFB2102703, 2020YFC1512001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Fisheye cameras are widely used in visual localization due to the advantage of the wide field of view. However, the severe distortion in fisheye images lead to feature matching difficulties. This paper proposes an IMU-assisted fisheye image matching method called spherically optimized random sample consensus (So-RANSAC). We converted the putative correspondences into fisheye spherical coordinates and then used an inertial measurement unit (IMU) to provide relative rotation angles to assist fisheye image epipolar constraints and improve the accuracy of pose estimation and mismatch removal. To verify the performance of So-RANSAC, experiments were performed on fisheye images of urban drainage pipes and public data sets. The experimental results showed that So-RANSAC can effectively improve the mismatch removal accuracy, and its performance was superior to the commonly used fisheye image matching methods in various experimental scenarios.<\/jats:p>","DOI":"10.3390\/rs13102017","type":"journal-article","created":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T11:45:57Z","timestamp":1621511157000},"page":"2017","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Spherically Optimized RANSAC Aided by an IMU for Fisheye Image Matching"],"prefix":"10.3390","volume":"13","author":[{"given":"Anbang","family":"Liang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"given":"Qingquan","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8537-2409","authenticated-orcid":false,"given":"Zhipeng","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Dejin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Jiasong","family":"Zhu","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9364-1784","authenticated-orcid":false,"given":"Jianwei","family":"Yu","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Xu","family":"Fang","sequence":"additional","affiliation":[{"name":"Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,20]]},"reference":[{"key":"ref_1","unstructured":"Zhang, Z., Rebecq, H., Forster, C., and Scaramuzza, D. (2016, January 16\u201321). Benefit of Large Field-of-View Cameras for Visual Odometry. Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1049\/iet-its:20080017","article-title":"Wide-Angle Camera Technology for Automotive Applications: A Review","volume":"3","author":"Hughes","year":"2009","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.measurement.2012.05.032","article-title":"State of the Art Review of Inspection Technologies for Condition Assessment of Water Pipes","volume":"46","author":"Liu","year":"2013","journal-title":"Measurement"},{"key":"ref_4","first-page":"49","article-title":"Pipeline Reconstruction from Fisheye Images","volume":"19","author":"Zhang","year":"2011","journal-title":"J. WSCG 9"},{"key":"ref_5","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","author":"Nister","year":"2004","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/s11263-020-01359-2","article-title":"Image Matching from Handcrafted to Deep Features: A Survey","volume":"129","author":"Ma","year":"2021","journal-title":"Int. J. Comput. Vis."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Scaramuzza, D., Martinelli, A., and Siegwart, R. (2006, January 4\u20137). A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion. Proceedings of the Fourth IEEE International Conference on Computer Vision Systems (ICVS\u201906), New York, NY, USA.","DOI":"10.1109\/ICVS.2006.3"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1109\/TPAMI.2006.153","article-title":"A Generic Camera Model and Calibration Method for Conventional, Wide-Angle, and Fish-Eye Lenses","volume":"28","author":"Kannala","year":"2006","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.cviu.2011.08.003","article-title":"Calibration of Omnidirectional Cameras in Practice: A Comparison of Methods","volume":"116","author":"Puig","year":"2012","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.isprsjprs.2019.11.016","article-title":"A UAV-Based Panoramic Oblique Photogrammetry (POP) Approach Using Spherical Projection","volume":"159","author":"Zhang","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1745","DOI":"10.1109\/TMM.2013.2280249","article-title":"Cube2Video: Navigate Between Cubic Panoramas in Real-Time","volume":"15","author":"Zhao","year":"2013","journal-title":"IEEE Trans. Multimed."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1109\/TCE.2007.4429204","article-title":"Panorama Mosaic Optimization for Mobile Camera Systems","volume":"53","author":"Ha","year":"2007","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1023\/A:1008184124789","article-title":"Spherical Mosaics with Quaternions and Dense Correlation","volume":"37","author":"Coorg","year":"2000","journal-title":"Int. J. Comput. Vis."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive Image Features from Scale-Invariant Keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_15","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_16","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.jvcir.2017.03.019","article-title":"Distortion Adaptive Sobel Filters for the Gradient Estimation of Wide Angle Images","volume":"46","author":"Furnari","year":"2017","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1832","DOI":"10.1109\/TPAMI.2014.2306421","article-title":"Scale Space for Camera Invariant Features","volume":"36","author":"Puig","year":"2014","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s11263-005-3848-x","article-title":"A Comparison of Affine Region Detectors","volume":"65","author":"Mikolajczyk","year":"2005","journal-title":"Int. J. Comput. Vis."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1109\/TIP.2016.2627816","article-title":"Affine Covariant Features for Fisheye Distortion Local Modeling","volume":"26","author":"Furnari","year":"2017","journal-title":"IEEE Trans. Image Process."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2412","DOI":"10.1109\/TIP.2012.2185937","article-title":"Scale-Invariant Features and Polar Descriptors in Omnidirectional Imaging","volume":"21","author":"Arican","year":"2012","journal-title":"IEEE Trans. Image Process."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/s11263-011-0505-4","article-title":"Scale Invariant Feature Transform on the Sphere: Theory and Applications","volume":"98","author":"Bogdanova","year":"2012","journal-title":"Int. J. Comput. Vis."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"752","DOI":"10.1109\/TRO.2012.2184952","article-title":"SRD-SIFT: Keypoint Detection and Matching in Images with Radial Distortion","volume":"28","author":"Lourenco","year":"2012","journal-title":"IEEE Trans. Robot."},{"key":"ref_23","unstructured":"Fitzgibbon, A.W. (2001, January 8\u201314). Simultaneous Linear Estimation of Multiple View Geometry and Lens Distortion. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, Kauai, HI, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1706","DOI":"10.1109\/TIP.2014.2307478","article-title":"Robust Point Matching via Vector Field Consensus","volume":"23","author":"Ma","year":"2014","journal-title":"IEEE Trans. Image Process."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1007\/s11263-018-1117-z","article-title":"Locality Preserving Matching","volume":"127","author":"Ma","year":"2019","journal-title":"Int. J. Comput. Vis."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.isprsjprs.2019.05.006","article-title":"LAM: Locality Affine-Invariant Feature Matching","volume":"154","author":"Li","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"813","DOI":"10.14358\/PERS.83.12.813","article-title":"4FP-Structure: A Robust Local Region Feature Descriptor","volume":"83","author":"Li","year":"2017","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Campos, M.B., Tommaselli, A.M.G., Castanheiro, L.F., Oliveira, R.A., and Honkavaara, E. (2019). A Fisheye Image Matching Method Boosted by Recursive Search Space for Close Range Photogrammetry. Remote Sens., 11.","DOI":"10.3390\/rs11121404"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Scaramuzza, D., Fraundorfer, F., and Siegwart, R. (2009, January 12\u201317). Real-Time Monocular Visual Odometry for on-Road Vehicles with 1-Point RANSAC. Proceedings of the 2009 IEEE International Conference on Robotics and Automation, Kobe, Japan.","DOI":"10.1109\/ROBOT.2009.5152255"},{"key":"ref_30","unstructured":"Li, B., Heng, L., Lee, G.H., and Pollefeys, M. (2013, January 3\u20137). A 4-Point Algorithm for Relative Pose Estimation of a Calibrated Camera with a Known Relative Rotation Angle. Proceedings of the 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Valiente, D., Gil, A., Reinoso, \u00d3., Juli\u00e1, M., and Holloway, M. (2017). Improved Omnidirectional Odometry for a View-Based Mapping Approach. Sensors, 17.","DOI":"10.3390\/s17020325"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Yi, K.M., Trulls, E., Ono, Y., Lepetit, V., Salzmann, M., and Fua, P. (2018). Learning to find good correspondences. arXiv.","DOI":"10.1109\/CVPR.2018.00282"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Pourian, N., and Nestares, O. (2019, January 22\u201325). An End to End Framework to High Performance Geometry-Aware Multi-Scale Keypoint Detection and Matching in Fisheye Imag. Proceedings of the 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan.","DOI":"10.1109\/ICIP.2019.8803707"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Liu, S., Guo, P., Feng, L., and Yang, A. (2019). Accurate and Robust Monocular SLAM with Omnidirectional Cameras. Sensors, 19.","DOI":"10.3390\/s19204494"},{"key":"ref_35","unstructured":"Chen, H.H. (1991, January 3\u20136). A Screw Motion Approach to Uniqueness Analysis of Head-Eye Geometry. Proceedings of the 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Maui, HI, USA."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Madgwick, S.O.H., Harrison, A.J.L., and Vaidyanathan, R. (July, January 29). Estimation of IMU and MARG Orientation Using a Gradient Descent Algorithm. Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, Switzerland.","DOI":"10.1109\/ICORR.2011.5975346"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Hartley, R., and Zisserman, A. (2003). Multiple View Geometry in Computer Vision, Cambridge University Press.","DOI":"10.1017\/CBO9780511811685"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Iachello, F. (2015). Lie Algebras and Applications, Springer. Lecture Notes in Physics.","DOI":"10.1007\/978-3-662-44494-8"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3693","DOI":"10.1109\/LRA.2018.2855443","article-title":"Omnidirectional DSO: Direct Sparse Odometry With Fisheye Cameras","volume":"3","author":"Matsuki","year":"2018","journal-title":"IEEE Robot. Autom. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/10\/2017\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:04:48Z","timestamp":1760162688000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/10\/2017"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,20]]},"references-count":39,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13102017"],"URL":"https:\/\/doi.org\/10.3390\/rs13102017","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,20]]}}}