{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:32:08Z","timestamp":1760239928759,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,1,30]],"date-time":"2019-01-30T00:00:00Z","timestamp":1548806400000},"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>We present a novel calibration method for a multi-view laser Doppler speed sensing (MLDSS) system. In contrast with the traditional method where only the laser geometry is independently calibrated, the proposed method simultaneously optimizes all the laser parameters and directly associates the parameters with a motion sensing model. By jointly considering the consistency among laser Doppler velocimetry, the laser geometry and a visual marker tracking system, the proposed calibration method further boosts the accuracy of MLDSS. We analyzed the factors influencing the precision, and quantitatively evaluated the efficiency of the proposed method on several data sets.<\/jats:p>","DOI":"10.3390\/s19030582","type":"journal-article","created":{"date-parts":[[2019,1,30]],"date-time":"2019-01-30T10:58:27Z","timestamp":1548845907000},"page":"582","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Visual Calibration for Multiview Laser Doppler Speed Sensing"],"prefix":"10.3390","volume":"19","author":[{"given":"Yunpu","family":"Hu","sequence":"first","affiliation":[{"name":"Department of Creative Informatics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan"}]},{"given":"Leo","family":"Miyashita","sequence":"additional","affiliation":[{"name":"Department of Creative Informatics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan"}]},{"given":"Yoshihiro","family":"Watanabe","sequence":"additional","affiliation":[{"name":"Department of Information and Communications Engineering, School of Engineering, Tokyo Institute of Technology, 4259-G2-31, Nagatsuta, Midori-ku, Yokohama, Kanagawa 226-8502, Japan"}]},{"given":"Masatoshi","family":"Ishikawa","sequence":"additional","affiliation":[{"name":"Department of Creative Informatics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"30371","DOI":"10.1364\/OE.25.030371","article-title":"Robust 6-DOF motion sensing for an arbitrary rigid body by multi-view laser Doppler measurements","volume":"25","author":"Hu","year":"2017","journal-title":"Opt. Express"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1782","DOI":"10.1109\/TIE.2008.2010166","article-title":"A Fastening Tool Tracking System Using an IMU and a Position Sensor With Kalman Filters and a Fuzzy Expert System","volume":"56","author":"Won","year":"2009","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Yi, C., Ma, J., Guo, H., Han, J., Gao, H., Jiang, F., and Yang, C. (2018). Estimating Three-Dimensional Body Orientation Based on an Improved Complementary Filter for Human Motion Tracking. Sensors, 18.","DOI":"10.3390\/s18113765"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1109\/34.121791","article-title":"A method for registration of 3-D shapes","volume":"14","author":"Besl","year":"1992","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_5","unstructured":"Chetverikov, D., Svirko, D., Stepanov, D., and Krsek, P. (2002, January 11\u201315). The Trimmed Iterative Closest Point algorithm. Proceedings of the 16th International Conference on Pattern Recognition, Quebec City, QC, Canada."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2410","DOI":"10.1109\/TVCG.2017.2734599","article-title":"Deep 6-DOF Tracking","volume":"23","author":"Garon","year":"2017","journal-title":"IEEE Trans. Vis. Comput. Gr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1109\/TPAMI.2017.2658577","article-title":"Direct Sparse Odometry","volume":"40","author":"Engel","year":"2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Hu, Y., Miyashita, L., Watanabe, Y., and Ishikawa, M. (2018, January 21\u201326). GLATUI: Non-intrusive Augmentation of Motion-based Interactions Using a GLDV. Proceedings of the Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI E \u201918), Montreal, QC, Canada.","DOI":"10.1145\/3170427.3188482"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1016\/j.ymssp.2007.08.008","article-title":"Avoidance of speckle noise in laser vibrometry by the use of kurtosis ratio: Application to mechanical fault diagnostics","volume":"22","author":"Vass","year":"2008","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4523","DOI":"10.1364\/AO.45.004523","article-title":"Numerical simulation of speckle noise in laser vibrometry","volume":"45","author":"Rothberg","year":"2006","journal-title":"Appl. Opt."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Chang, Y.H., Liu, C.S., and Cheng, C.C. (2018). Design and Characterisation of a Fast Steering Mirror Compensation System Based on Double Porro Prisms by a Screw-Ray Tracing Method. Sensors, 18.","DOI":"10.3390\/s18114046"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"122408","DOI":"10.1117\/1.OE.53.12.122408","article-title":"Numerical and experimental characterization of reducing geometrical fluctuations of laser beam based on rotating optical diffuser","volume":"53","author":"Liu","year":"2014","journal-title":"Opt. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sels, S., Bogaerts, B., Vanlanduit, S., and Penne, R. (2018). Extrinsic Calibration of a Laser Galvanometric Setup and a Range Camera. Sensors, 18.","DOI":"10.3390\/s18051478"},{"key":"ref_14","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_15","doi-asserted-by":"crossref","first-page":"5709","DOI":"10.1109\/JSEN.2015.2447835","article-title":"Data-Driven Learning for Calibrating Galvanometric Laser Scanners","volume":"15","author":"Wissel","year":"2015","journal-title":"IEEE Sens. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4941","DOI":"10.1364\/OL.43.004941","article-title":"Design and simplified calibration of a Mueller imaging polarimeter for material classification","volume":"43","author":"Leporcq","year":"2018","journal-title":"Opt. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Triggs, B., Zisserman, A., and Szeliski, R. (2000). Bundle Adjustment\u2014A Modern Synthesis. Vision Algorithms: Theory and Practice, Springer.","DOI":"10.1007\/3-540-44480-7"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2097","DOI":"10.1109\/TPAMI.2012.18","article-title":"A Minimal Solution for the Extrinsic Calibration of a Camera and a Laser-Rangefinder","volume":"34","author":"Vasconcelos","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Scaramuzza, D., Harati, A., and Siegwart, R. (November, January 29). Extrinsic self calibration of a camera and a 3D laser range finder from natural scenes. Proceedings of the 2007 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS\u201907), San Diego, CA, USA.","DOI":"10.1109\/IROS.2007.4399276"},{"key":"ref_20","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":"2008","journal-title":"Int. J. Comput. Vis."},{"key":"ref_21","unstructured":"Trucco, E., and Verri, A. (1998). Introductory Techniques for 3-D Computer Vision, Prentice Hall."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1137\/0111030","article-title":"An Algorithm for Least-Squares Estimation of Nonlinear Parameters","volume":"11","author":"Marquardt","year":"1963","journal-title":"J. Soc. Ind. Appl. Math."},{"key":"ref_23","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_24","unstructured":"Heikkila, J., and Silven, O. (1997, January 17\u201319). A four-step camera calibration procedure with implicit image correction. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, PR, USA."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1214\/aoms\/1177703732","article-title":"Robust Estimation of a Location Parameter","volume":"35","author":"Huber","year":"1964","journal-title":"Ann. Math. Stat."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/3\/582\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:29:44Z","timestamp":1760185784000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/3\/582"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,30]]},"references-count":25,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2019,2]]}},"alternative-id":["s19030582"],"URL":"https:\/\/doi.org\/10.3390\/s19030582","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,1,30]]}}}