Color Supported Generalized-ICP

Michael Korn, Martin Holzkothen, Josef Pauli

2014

Abstract

This paper presents a method to support point cloud registration with color information. For this purpose we integrate L*a*b* color space information into the Generalized Iterative Closest Point (GICP) algorithm, a state-of-the-art Plane-To-Plane ICP variant. A six-dimensional k-d tree based nearest neighbor search is used to match corresponding points between the clouds. We demonstrate that the additional effort in general does not have an immoderate impact on the runtime, since the number of iterations can be reduced. The influence on the estimated 6 DoF transformations is quantitatively evaluated on six different datasets. It will be shown that the modified algorithm can improve the results without needing any special parameter adjustment.

References

  1. Bentley, J. L. (1975). Multidimensional binary search trees used for associative searching. Communications of the ACM, 18(9):509-517.
  2. Besl, P. J. and McKay, N. D. (1992). A method for registration of 3-d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2):239-256.
  3. Druon, S., Aldon, M. J., and Crosnier, A. (2006). Color constrained icp for registration of large unstructured 3d color data sets. In Proc. of the IEEE International Conference on Information Acquisition, pages 249- 255.
  4. Johnson, A. E. and Kang, S. B. (1999). Registration and integration of textured 3d data. Image and Vision Computing, 17:135-147.
  5. Joung, J., An, K. H., Kang, J. W., Chung, M.-J., and Yu, W. (2009). 3d environment reconstruction using modified color icp algorithm by fusion of a camera and a 3d laser range finder. In Intelligent Robots and Systems, pages 3082-3088.
  6. Macedo-Cruz, A., Pajares, G., Santos, M., and VillegasRomero, I. (2011). Digital image sensor-based assessment of the status of oat (avena sativa l.) crops after frost damage. Sensors, 11(6):6015-6036.
  7. Men, H., Gebre, B., and Pochiraju, K. (2011). Color point cloud registration with 4d icp algorithm. In Proc. of the IEEE International Conference on Robotics and Automation, pages 1511-1516.
  8. Paschos, G. (2001). Perceptually uniform color spaces for color texture analysis: An empirical evaluation. IEEE Transactions on Image Processing, 10(6):932-937.
  9. Rusinkiewicz, S. and Levoy, M. (2001). Efficient variants of the icp algorithm. In Proc. of the 3rd International Conference on 3-D Digital Imaging and Modeling, pages 145-152.
  10. Rusu, R. B. and Cousins, S. (2011). 3D is here: Point Cloud Library (PCL). In International Conference on Robotics and Automation, Shanghai, China.
  11. Salvi, J., Matabosch, C., Fofi, D., and Forest, J. (2007). A review of recent range image registration methods with accuracy evaluation. Image and Vision Computing, 25:578 - 596.
  12. Segal, A., Haehnel, D., and Thrun, S. (2009). Generalizedicp. Robotics: Science and Systems V.
  13. Sturm, J., Engelhard, N., Endres, F., Burgard, W., and Cremers, D. (2012). A benchmark for the evaluation of rgb-d slam systems. In Proc. of the International Conference on Intelligent Robot Systems (IROS).
  14. Zhang, Z. (1994). Iterative point matching for registration of free-form curves and surfaces. International Journal of Computer Vision, 13(2):119-152.
Download


Paper Citation


in Harvard Style

Korn M., Holzkothen M. and Pauli J. (2014). Color Supported Generalized-ICP . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-009-3, pages 592-599. DOI: 10.5220/0004692805920599


in Bibtex Style

@conference{visapp14,
author={Michael Korn and Martin Holzkothen and Josef Pauli},
title={Color Supported Generalized-ICP},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={592-599},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004692805920599},
isbn={978-989-758-009-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2014)
TI - Color Supported Generalized-ICP
SN - 978-989-758-009-3
AU - Korn M.
AU - Holzkothen M.
AU - Pauli J.
PY - 2014
SP - 592
EP - 599
DO - 10.5220/0004692805920599