{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T18:22:16Z","timestamp":1772302936384,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T00:00:00Z","timestamp":1579651200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National key Research and Development Program of China","award":["Grant No. 2018YFB1308000"],"award-info":[{"award-number":["Grant No. 2018YFB1308000"]}]},{"name":"the Special Program for Science and Technology of National Regional Innovation Center of Weihai City","award":["Grant No. 2017QYCX10"],"award-info":[{"award-number":["Grant No. 2017QYCX10"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant No. 51905119"],"award-info":[{"award-number":["Grant No. 51905119"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Fundamental Research Funds for Central Universities","award":["Grant No. HIT.NSRIF.2020090"],"award-info":[{"award-number":["Grant No. HIT.NSRIF.2020090"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The calibration problem of binocular stereo vision rig is critical for its practical application. However, most existing calibration methods are based on manual off-line algorithms for specific reference targets or patterns. In this paper, we propose a novel simultaneous localization and mapping (SLAM)-based self-calibration method designed to achieve real-time, automatic and accurate calibration of the binocular stereo vision (BSV) rig\u2019s extrinsic parameters in a short period without auxiliary equipment and special calibration markers, assuming the intrinsic parameters of the left and right cameras are known in advance. The main contribution of this paper is to use the SLAM algorithm as our main tool for the calibration method. The method mainly consists of two parts: SLAM-based construction of 3D scene point map and extrinsic parameter calibration. In the first part, the SLAM mainly constructs a 3D feature point map of the natural environment, which is used as a calibration area map. To improve the efficiency of calibration, a lightweight, real-time visual SLAM is built. In the second part, extrinsic parameters are calibrated through the 3D scene point map created by the SLAM. Ultimately, field experiments are performed to evaluate the feasibility, repeatability, and efficiency of our self-calibration method. The experimental data shows that the average absolute error of the Euler angles and translation vectors obtained by our method relative to the reference values obtained by Zhang\u2019s calibration method does not exceed 0.5\u02da and 2 mm, respectively. The distribution range of the most widely spread parameter in Euler angles is less than 0.2\u02da while that in translation vectors does not exceed 2.15 mm. Under the general texture scene and the normal driving speed of the mobile robot, the calibration time can be generally maintained within 10 s. The above results prove that our proposed method is reliable and has practical value.<\/jats:p>","DOI":"10.3390\/s20030621","type":"journal-article","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T11:17:57Z","timestamp":1579691877000},"page":"621","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["SLAM-Based Self-Calibration of a Binocular Stereo Vision Rig in Real-Time"],"prefix":"10.3390","volume":"20","author":[{"given":"Hesheng","family":"Yin","sequence":"first","affiliation":[{"name":"State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhe","family":"Ma","sequence":"additional","affiliation":[{"name":"Industrial Research Institute of Robotics and Intelligent Equipment, Harbin Institute of Technology, Weihai 264209, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1612-0459","authenticated-orcid":false,"given":"Ming","family":"Zhong","sequence":"additional","affiliation":[{"name":"Industrial Research Institute of Robotics and Intelligent Equipment, Harbin Institute of Technology, Weihai 264209, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kuan","family":"Wu","sequence":"additional","affiliation":[{"name":"Sphyrna Technology Company, Beijing 100096, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuteng","family":"Wei","sequence":"additional","affiliation":[{"name":"Sphyrna Technology Company, Beijing 100096, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junlong","family":"Guo","sequence":"additional","affiliation":[{"name":"Industrial Research Institute of Robotics and Intelligent Equipment, Harbin Institute of Technology, Weihai 264209, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1109\/TITS.2008.2006736","article-title":"Binocular spherical stereo","volume":"9","author":"Li","year":"2008","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tu, J., and Zhang, L. (2018). Effective data-driven calibration for a galvanometric laser scanning system using binocular stereo vision. Sensors, 18.","DOI":"10.3390\/s18010197"},{"key":"ref_3","unstructured":"Heng, L., B\u00fcrki, M., Lee, G.H., Furgale, P., Siegwart, R., and Pollefeys, M. (June, January 31). Infrastructure-based calibration of a multi-camera rig. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Gil, G., Savino, G., Piantini, S., and Pierini, M. (2018). Motorcycles that see: Multifocal stereo vision sensor for advanced safety systems in tilting vehicles. Sensors, 18.","DOI":"10.3390\/s18010295"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"094109","DOI":"10.1117\/1.OE.58.9.094109","article-title":"Mirror binocular calibration method based on sole principal point","volume":"58","author":"Chai","year":"2019","journal-title":"Opt. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1016\/j.procir.2015.12.108","article-title":"Analysis of camera calibration with respect to measurement accuracy","volume":"41","author":"Semeniuta","year":"2016","journal-title":"Procedia Cirp"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"103","DOI":"10.14358\/PERS.81.2.103","article-title":"Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry","volume":"81","author":"Karara","year":"2015","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MIM.2015.7335836","article-title":"Calibration of low-cost triaxial inertial sensors","volume":"18","author":"Rohac","year":"2015","journal-title":"IEEE Instrum. Meas. Mag."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Wu, D., Chen, T., and Li, A. (2016). A high precision approach to calibrate a structured light vision sensor in a robot-based three-dimensional measurement system. Sensors, 16.","DOI":"10.3390\/s16091388"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1016\/j.neucom.2015.03.119","article-title":"A novel camera calibration technique based on differential evolution particle swarm optimization algorithm","volume":"174","author":"Deng","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1109\/70.795794","article-title":"Iterative multistep explicit camera calibration","volume":"15","author":"Batista","year":"1999","journal-title":"IEEE Trans. Rob. Autom."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1109\/70.544775","article-title":"Camera calibration with a near-parallel (ill-conditioned) calibration board configuration","volume":"12","author":"Zhuang","year":"1996","journal-title":"IEEE Trans. Rob. Autom."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"22254","DOI":"10.1364\/OE.27.022254","article-title":"Stereo calibration with absolute phase target","volume":"27","author":"Wang","year":"2019","journal-title":"Opt. Express"},{"key":"ref_14","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. Mach. Intell."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1117\/1.2352738","article-title":"Robust recognition of checkerboard pattern for camera calibration","volume":"45","author":"Yu","year":"2006","journal-title":"Opt. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Chen, Q., Wu, H., and Wada, T. (2004, January 11\u201314). Camera calibration with two arbitrary coplanar circles. Proceedings of the European Conference on Computer Vision, Berlin, Germany.","DOI":"10.1007\/978-3-540-24672-5_41"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Kumar, R.K., Ilie, A., Frahm, J.M., and Pollefeys, M. (2008, January 23\u201328). Simple calibration of non-overlapping cameras with a mirror. Proceedings of the Proc IEEE Conference on Computer Vision & Pattern Recognition, Anchorage, AK, USA.","DOI":"10.1109\/CVPR.2008.4587676"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Su, P.C., Shen, J., Xu, W., Cheung, S.S., and Luo, Y. (2018). A Fast and Robust Extrinsic Calibration for RGB-D Camera Networks. Sensors, 18.","DOI":"10.3390\/s18010235"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wei, Z., and Zhao, K. (2016). Structural Parameters Calibration for Binocular Stereo Vision Sensors Using a Double-Sphere Target. Sensors, 16.","DOI":"10.3390\/s16071074"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Luong, Q.-T., and Faugeras, O.D. (2001). Self-calibration of a stereo rig from unknown camera motions and point correspondences. Calibration and Orientation of Cameras in Computer Vision, Springer.","DOI":"10.1007\/978-3-662-04567-1_8"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2012","DOI":"10.1109\/TIP.2009.2024578","article-title":"N-SIFT: N-dimensional Scale Invariant Feature Transform","volume":"18","author":"Cheung","year":"2009","journal-title":"IEEE Trans. Image Process."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, Z., and Tang, Q. (2016, January 6\u20138). Camera self-calibration based on multiple view images. Proceedings of the Nicograph International (NicoInt), Hangzhou, China.","DOI":"10.1109\/NicoInt.2016.16"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1142\/S230138501540004X","article-title":"An automatic self-calibration approach for wide baseline stereo cameras using sea surface images","volume":"3","author":"Wang","year":"2015","journal-title":"Unmanned Systs."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.jvcir.2016.05.003","article-title":"A flexible technique based on fundamental matrix for camera self-calibration with variable intrinsic parameters from two views. J","volume":"39","author":"Boudine","year":"2016","journal-title":"Visual Commun. Image Represent."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.isprsjprs.2019.11.014","article-title":"Panoramic SLAM from a multiple fisheye camera rig","volume":"159","author":"Ji","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, X., Wan, Z., and Zhang, J. (2018). A Method for Extrinsic Parameter Calibration of Rotating Binocular Stereo Vision Using a Single Feature Point. Sensors, 18.","DOI":"10.3390\/s18113666"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Carrera, G., Angeli, A., and Davison, A.J. (2011, January 9\u201313). SLAM-based automatic extrinsic calibration of a multi-camera rig. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980294"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","article-title":"Speeded-up robust features (SURF)","volume":"110","author":"Bay","year":"2008","journal-title":"Comput. Vision Image Understanding"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s10514-015-9466-8","article-title":"Self-calibration and visual SLAM with a multi-camera system on a micro aerial vehicle","volume":"39","author":"Heng","year":"2015","journal-title":"Auton. Rob."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"775","DOI":"10.1002\/rob.21540","article-title":"Leveraging Image-based Localization for Infrastructure-based Calibration of a Multi-camera Rig","volume":"32","author":"Heng","year":"2015","journal-title":"J. Field Rob."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1007\/s11554-014-0415-0","article-title":"Video Extruder: A semi-dense point tracker for extracting beams of trajectories in real time","volume":"11","author":"Garrigues","year":"2016","journal-title":"J. Real-Time Image Proc."},{"key":"ref_32","unstructured":"Derpanis, K.G. (2020, January 22). The harris corner detector. Available online: http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.482.1724&rep=rep1&type=pdf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1109\/TIP.2015.2431445","article-title":"Feature-based Lucas-Kanade and active appearance models","volume":"24","author":"Antonakos","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Krig, S. (2016). Interest point detector and feature descriptor survey. Computer vision metrics, Springer.","DOI":"10.1007\/978-3-319-33762-3"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.patrec.2018.02.020","article-title":"Efficient adaptive non-maximal suppression algorithms for homogeneous spatial keypoint distribution","volume":"106","author":"Bailo","year":"2018","journal-title":"Pattern Recognit. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Bian, J., Lin, W.-Y., Matsushita, Y., Yeung, S.-K., Nguyen, T.-D., and Cheng, M.-M. (2017, January 21\u201326). Gms: Grid-based motion statistics for fast, ultra-robust feature correspondence. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.302"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1109\/TPAMI.2003.1217599","article-title":"Complete solution classification for the perspective-three-point problem","volume":"25","author":"Gao","year":"2003","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Chum, O., Matas, J., and Kittler, J. (2003, January 10\u201312). Locally optimized RANSAC. Proceedings of the Joint Pattern Recognition Symposium, Berlin, Germany.","DOI":"10.1007\/978-3-540-45243-0_31"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1109\/TIE.2012.2183833","article-title":"Real-Time Nonlinear Parameter Estimation Using the Levenberg\u2013Marquardt Algorithm on Field Programmable Gate Arrays","volume":"60","author":"Shawash","year":"2013","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Strasdat, H., Davison, A.J., Montiel, J.M.M., and Konolige, K. (2011, January 6\u201313). Double window optimisation for constant time visual SLAM. Proceedings of the IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126517"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.robot.2017.03.018","article-title":"Multi-camera visual SLAM for autonomous navigation of micro aerial vehicles","volume":"93","author":"Yang","year":"2017","journal-title":"Rob. Autom. Syst."},{"key":"ref_42","unstructured":"H\u00e4rdle, W., and Gasser, T. (1985). On robust kernel estimation of derivatives of regression functions. Scand. J. Stat., 233\u2013240."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Strasdat, H., Montiel, J., and Davison, A.J. (2010). Scale drift-aware large scale monocular SLAM. Robotics: Science and Systems VI, The Mit Press.","DOI":"10.15607\/RSS.2010.VI.010"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/j.ymssp.2018.02.038","article-title":"Direction cosine matrix estimation with an inertial measurement unit","volume":"109","author":"Wang","year":"2018","journal-title":"Mech. Syst. Sig. Process."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1007\/s001380050120","article-title":"A compact algorithm for rectification of stereo pairs","volume":"12","author":"Fusiello","year":"2000","journal-title":"Mach. Vision Appl."},{"key":"ref_46","unstructured":"Hartley, R., and Gupta, R. (1993, January 15\u201317). Computing matched-epipolar projections. Proceedings of the IEEE Computer Society Conference on Computer Vision & Pattern Recognition (CVPR), New York, NY, USA."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1118\/1.596078","article-title":"Image intensifier distortion correction","volume":"14","author":"Chakraborty","year":"1987","journal-title":"Med. Phys."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/3\/621\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:44:27Z","timestamp":1760363067000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/3\/621"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,22]]},"references-count":47,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["s20030621"],"URL":"https:\/\/doi.org\/10.3390\/s20030621","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,22]]}}}