Abstract
Recognizing the arbitrary standard FIFA ball is a significant ability for soccer robots to play competition without the constraint of current color-coded environment. This paper describes a novel method to recognize arbitrary FIFA ball based on omni-directional vision system. Firstly the omni-directional vision system and its calibration for distance map are introduced, and the conclusion that the ball on the field can be imaged to be ellipse approximately is derived by analyzing the imaging character. Then the arbitrary FIFA ball is detected by using image processing algorithm to search the ellipse imaged by the ball according to the derivation. In the actual application, a simple but effective ball tracking algorithm is also used to reduce the running time needed after the ball has been recognized globally. The experiment results show that the novel method can recognize the arbitrary FIFA ball effectively and in real-time.
Chapter PDF
Similar content being viewed by others
Keywords
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.
References
Hanek, R., Beetz, M.: The Contracting Curve Density Algorithm: Fitting Parametric Curve Models to Images Using Local Self-Adapting Separation Criteria. International Journal of Computer Vision 59, 233–258 (2004)
Hanek, R., Schmitt, T., Buck, S., Beetz, M.: Fast Image-based Object Localization in Natural Scenes. In: Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 116–122 (2002)
Hanek, R., Schmitt, T., Buck, S., Beetz, M.: Towards RoboCup without Color Labeling. In: Kaminka, G.A., Lima, P.U., Rojas, R. (eds.) RoboCup 2002. LNCS, vol. 2752, pp. 179–194. Springer, Heidelberg (2003)
Treptow, A., Zell, A.: Real-time object tracking for soccer-robots without color information. Robotics and Autonomous Systems 48, 41–48 (2004)
Mitri, S., Pervölz, K., Surmann, H., Nüchter, A.: Fast Color-Independent Ball Detection for Mobile Robots. In: Proceedings of IEEE Mechatronics and Robotics, pp. 900–905 (2004)
Mitri, S., Frintrop, S., Pervölz, K., Surmann, H., Nüchter, A.: Robust Object Detection at Regions of Interest with an Application in Ball Recognition. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 125–130 (2005)
Coath, G., Musumeci, P.: Adaptive Arc Fitting for Ball Detection in RoboCup. In: APRS Workshop on Digital Image Analysing (2003)
Zhang, H., Lu, H., Ji, X., et al.: NuBot Team Description Paper 2007. RoboCup 2007 Atlanta, Atlanta, USA (2007) CD-ROM
Benosman, R., Kang, S.B. (eds.): Panoramic Vision: Sensors, Theory and Applications. Springer, New York (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lu, H., Zhang, H., Xiao, J., Liu, F., Zheng, Z. (2009). Arbitrary Ball Recognition Based on Omni-Directional Vision for Soccer Robots. In: Iocchi, L., Matsubara, H., Weitzenfeld, A., Zhou, C. (eds) RoboCup 2008: Robot Soccer World Cup XII. RoboCup 2008. Lecture Notes in Computer Science(), vol 5399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02921-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-02921-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02920-2
Online ISBN: 978-3-642-02921-9
eBook Packages: Computer ScienceComputer Science (R0)