Robust and Accurate Detection of Object Orientation and ID Without Color Segmentation

  • Shoichi Shimizu
  • Tomoyuki Nagahashi
  • Hironobu Fujiyoshi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4020)

Abstract

This paper describes a novel approach to detecting orientation and identity of robots without color segmentation. The continuous DP matching calculates the similarity between the reference pattern and the input pattern by matching the intensity changes of the robot markers. After the continuous DP matching, a similarity value is used for object identification. Correspondences of the optimal route obtained by back tracing are used for estimating the robot’s orientation. This method archives orientation estimations of less than 1 degree and robustness with respect to varying light conditions.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bruce, J., Balch, T., Veloso, M.: Fast and Inexpensive Color Image Segmentation for Interactive Robots. In: Proceedings of IROS 2000, Japan (2000)Google Scholar
  2. 2.
    Egorova, A., Simon, M., Wiesel, F., Gloye, A., Rojas, R.: Plug and play: Fast automatic geometry and color calibration for cameras tracking robots. In: Nardi, D., Riedmiller, M., Sammut, C., Santos-Victor, J. (eds.) RoboCup 2004. LNCS, vol. 3276, pp. 394–401. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  3. 3.
    Murakami, K., Hibino, S., Kodama, Y., Iida, T., Kato, K., Naruse, T.: Cooperative Soccer Play by Real Small-Size Robot. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS, vol. 3020, pp. 410–421. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Ball, D., Wyeth, G., Nuske, S.: A Global Vision System for a Robot Soccer Team. In: Proceedings of the 2004 Australasian Conference on Robotics and Automation (ACRA) (2004)Google Scholar
  5. 5.
    Bruce, J., Veloso, M.: Fast and Accurate Vision-Based Pattern Detection and Identification. In: Proceedings of ICRA 2003, the 2003 IEEE International Conference on Robotics and Automation (ICRA 2003) (May 2003)Google Scholar
  6. 6.
    Hibino, S., Kodama, Y., Nagasaka, Y., Takahashi, T., Murakami, K., Naruse, T.: Fast Image Processing and Flexible Path Generation System for RoboCup Small Size League. In: Kaminka, G.A., Lima, P.U., Rojas, R. (eds.) RoboCup 2002. LNCS, vol. 2752, pp. 53–64. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  7. 7.
    Sakoe, H., Chiba, S.: Dynamic Programming Algorithm Optimization for Spoken Word Recognition. IEEE Trans. Acoust. Speech, and Signal Process ASSP-26, 43–49 (1978)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shoichi Shimizu
    • 1
  • Tomoyuki Nagahashi
    • 1
  • Hironobu Fujiyoshi
    • 1
  1. 1.Dept. of Computer ScienceChubu UniversityJapan

Personalised recommendations