Reconstruction of three-dimensional maps based on closed-form solutions of the variational problem of multisensor data registration

Cover Page

Cite item

Full Text

Abstract

A closed-form solution is proposed for the problem of minimizing a functional consisting of two terms measuring mean-square distances for visually associated characteristic points on an image and meansquare distances for point clouds in terms of a point-to-plane metric. An accurate method for reconstructing three-dimensional dynamic environment is presented, and the properties of closed-form solutions are described. The proposed approach improves the accuracy and convergence of reconstruction methods for complex and large-scale scenes.

About the authors

A. V. Vokhmintcev

Chelyabinsk State University; Institution of Higher Education Yugra State University

Author for correspondence.
Email: vav@csu.ru
Russian Federation, 129, Br.Kashirinykh street, Chelyabinsk, 454001; 16, Chekhova str., Khanty-Mansiysk, Khanty Mansiysk Autonomous okrug Yugra, Tyumen region, 628012

A. V. Melnikov

Chelyabinsk State University; Institution of Higher Education Yugra State University

Email: melnikovav@uriit.ru
Russian Federation, 129, Br.Kashirinykh street, Chelyabinsk, 454001; 16, Chekhova str., Khanty-Mansiysk, Khanty Mansiysk Autonomous okrug Yugra, Tyumen region, 628012

K. V. Mironov

Ural Federal University named after the first President of Russia B. N. Yeltsin; Ufa State Aviation Technical University

Email: mironov.kv@net.ugatu.su
Russian Federation, 51, Lenina ave., r. 262, Ekaterinburg, 620000; 12, Karl Marx str., Ufa, 450008

V. V. Burlutskiy

Institution of Higher Education Yugra State University

Email: burlutskyvv@uriit.ru
Russian Federation, 16, Chekhova str., Khanty-Mansiysk, Khanty Mansiysk Autonomous okrug Yugra, Tyumen region, 628012

References

  1. Henry P., Krainin M., Herbst E., Ren X., Fox D. RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments // Intern. J. Robotics Res. 2012. V. 31. № 5. P. 647-663. https://rse-lab.cs.washington.edu/postscripts/3d-mapping-iser10-final.pdf; https://dl.acm.org/citation.cfm?id=2190637.
  2. Besl P.J., McKay H.D. A Method for Registration of 3-D Shapes // IEEE Trans. Pattern Anal. and Machine Intelligence. 1992. V. 14. № 2. P. 239-256. https://ieeexplore.ieee.org/document/121791/similar#similar.
  3. Fuentes-Pacheco J., Ruiz-Ascencio J., Rendón-Mancha J.M. Visual Simultaneous Localization and Mapping: a Survey // Artificial Intelligence Rev. 2015. V. 43. № 1. P. 55-81. https://dl.acm.org/citation.cfm?id=2717465.
  4. Vokhmintsev A., Yakovlev K. A Real-Time Algorithm for Mobile Robot Mapping Based on Rotation Invariant Descriptors and ICP. Proc. 5th Analysis of Images, Social Networks and Texts. Communications in Computer and Information Science. № 661. Yakaterinburg: Springer, 2017. P. 357-369. https://link.springer.com/chapter/10.1007/978-3-319-52920-2_33.
  5. Lowe D.G. Distinctive Image Features from ScaleInvariant Keypoints // Intern. J. Computer Vision. 2004. V. 60. № 2. P. 91-110. https://link.springer.com/article/10.1023/B:VISI.0000029664.99615.94. РЕКОНСТРУКЦИЯ ТРЁХМЕРНЫХ СЦЕН НА ОСНОВЕ ТОЧНЫХ РЕШЕНИЙ... 677 ДОКЛАДЫ АКАДЕМИИ НАУК том 484 № 6 2019
  6. Horn B. Closed-Form Solution of Absolute Orientation Using Unit Quaternions // J. Opt. Soc. Amer. A. 1987. V. 4. № 4. P. 629-642. https://www.osapublishing.org/josaa/abstract.cfm?uri=josaa-4-4-629.
  7. Horn B., Hilden H., Negahdaripour S. Closed-Form Solution of Absolute Orientation Using Orthonormal Matrices // J. Opt. Soc. Amer. A. 1988. V. 5. № 7. P. 1127-1135. https://www.osapublishing.org/josaa/abstract.cfm?uri=josaa-5-7-1127.
  8. Du S., Zheng N., Meng G., Yuan Z. Affine Registration of Point Sets Using ICP and ICA // IEEE Signal Processing Lett. 2008. V. 15. P. 689-692. https://ieeexplore.ieee.org/document/4666764.
  9. Chen Y., Medioni G. Object Modeling by Registration of Multiple Range Images. IEEE Proceedings of Conference on Robotics and Automation. Sacramento: IEEE, 1991. P. 2724-2729. https://ieeexplore.ieee. org/abstract/document/132043.
  10. Rusinkiewicz S., Levoy M. Efficient Variants of the ICP Algorithm. IEEE Proceedings of the International Conference on 3-D Digital Imaging and Modeling. Quebec City: IEEE, 2001. P. 145-152. https://ieeexplore.ieee.org/abstract/document/924423.
  11. Petitot J. The Neurogeometry of Pinwheels as a SubRiemannian Contact Structure // J. Physiol. 2003. V. 97. № 2/3. P. 265-309. https://www.ncbi.nlm.nih.gov/pubmed/14766146.
  12. Vokhmintcev A., Timchenko M., Alina K. Real-Time Visual Loop-Closure Detection Using Fused Iterative Close Point Algorithm and Extended Kalman Filter. IEEE Proceedings of 3th Intern. Conf. on Industrial Engineering, Applications and Manufacturing (ICIEAM). St.-Petersburg: IEEE, 2017. https://ieeexplore.ieee.org/document/8076187.
  13. Вохминцев А.В., Соченков И.В., Кузнецов В.В., Тихоньких Д.В. // ДАН. 2016. Т. 466. № 3. С. 261-266.
  14. Echeagaray-Patron B.A., Kober V.I., Karnaukhov V.N., Kuznetsov V.V. A Method of Face Recognition Using 3D Facial Surfaces // J. Comms Technol. and Electronics. 2017. V. 62. № 6. P. 648-652. https://link.springer.com/article/10.1134/S1064226917060067.
  15. Vokhmintcev A., Botova T., Sochenkov I., Sochenkova A., Makovetskii A. Robot Mapping Algorithm Based on Kalman Filtering and Symbolic Tags. SPIE Proc. of Applications of Digital Image Processing XL, № 10396. San-Diego: SPIE, 2017. https://www.spiedigitallibrary.org/conference-proceedings-ofspie/10396/103962I/Robot-mapping-algorithm-basedon-Kalman-filtering-and-symbolic-tags/10.1117/12.2273562.short.

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2019 Russian academy of sciences

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies