Utilization of Colour in ICP-based Point Cloud Registration

  • Marta Łępicka
  • Tomasz Kornuta
  • Maciej Stefańczyk
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 403)


Advent of RGB-D sensors fostered the progress of computer vision algorithms spanning from object recognition, object and scene modelling to human activity recognition. This paper presents a new flavour of ICP algorithm developed for the purpose of pair-wise registration of colour point clouds generated from RGB-D images. After a brief introduction to the registration problem, we analyze the ICP algorithm and survey its different flavours in order to indicate potential methods of injecting of colour into it. Our consideration led to a solution, which we validate experimentally on colour point clouds from the publicly available dataset.


Root Mean Square Error Point Cloud Data Association Iterative Close Point Iterative Close Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors acknowledge the financial support of the National Centre for Research and Development grant no. PBS1/A3/8/2012.


  1. 1.
    Besl, P., McKay, N.: A method for registration of 3-d shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992)CrossRefGoogle Scholar
  2. 2.
    Chen, Y., Medioni, G.: Object modeling by registration of multiple range images. In: Proceedings of the 1991 IEEE International Conference on Robotics and Automation, pp. 2724–2729. IEEE (1991)Google Scholar
  3. 3.
    Godin, G., Rioux, M., Baribeau, R.: Three-dimensional registration using range and intensity information. In: Photonics for Industrial Applications. International Society for Optics and Photonics, pp. 279–290 (1994)Google Scholar
  4. 4.
    Johnson, A.E., Kang, S.B.: Registration and integration of textured 3d data. Image vis. comput. 17(2), 135–147 (1999)CrossRefGoogle Scholar
  5. 5.
    Kasprzak, W., Kornuta, T., Zieliński, C.: A virtual receptor in a robot control framework. In: Recent Advances in Automation, Robotics and Measuring Techniques. Advances in Intelligent Systems and Computing (AISC), Springer (2014)Google Scholar
  6. 6.
    Lai, K., Bo, L., Ren, X., Fox, D.: A large-scale hierarchical multi-view RGB-D object dataset. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 1817–1824. IEEE (2011)Google Scholar
  7. 7.
    Lai, K., Bo, L., Ren, X., Fox, D.: A scalable tree-based approach for joint object and pose recognition. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 1474–1480 (2011)Google Scholar
  8. 8.
    Men, H., Gebre, B., Pochiraju, K.: Color point cloud registration with 4d icp algorithm. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 1511–1516. IEEE (2011)Google Scholar
  9. 9.
    Nistér, D., Naroditsky, O., Bergen, J.: Visual odometry. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004, vol. 1, I-652 p. IEEE (2004)Google Scholar
  10. 10.
    Pomerleau, F., Colas, F., Siegwart, R., Magnenat, S.: Comparing icp variants on real-world data sets. Auton. Robot. 34(3), 133–148 (2013)CrossRefGoogle Scholar
  11. 11.
    Ren, X., Fox, D., Konolige, K.: Change their perception: RGB-D for 3-D modeling and recognition. IEEE Robot. Autom. Mag 20(4), 49–59 (2013)CrossRefGoogle Scholar
  12. 12.
    Rusinkiewicz, S., Levoy, M.: Efficient variants of the icp algorithm. In: Proceedings of the Third International Conference on 3-D Digital Imaging and Modeling, 2001, pp. 145–152. IEEE (2001)Google Scholar
  13. 13.
    Stefańczyk, M., Kornuta, T.: Handling of asynchronous data flow in robot perception subsystems. In: Simulation, Modeling, and Programming forAutonomous Robots. Lecture Notes in Computer Science, vol. 8810, pp. 509–520. Springer (2014)Google Scholar
  14. 14.
    Xie, Z., Singh, A., Uang, J., Narayan, K.S., Abbeel, P.: Multimodal blending for high-accuracy instance recognition. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2214–2221. IEEE (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Marta Łępicka
    • 1
  • Tomasz Kornuta
    • 1
  • Maciej Stefańczyk
    • 1
  1. 1.Institute of Control and Computation EngineeringWarsaw University of TechnologyWarsawPoland

Personalised recommendations