JACIII Vol.18 No.5 pp. 776-783
doi: 10.20965/jaciii.2014.p0776


Synchronized Dual Camera Vision System for Locating and Identify Highly Dynamic Objects

Noel S. Gunay, Elmer P. Dadios, Ryan Rhay P. Vicerra,
Argel A. Bandala, and Laurence A. Gan Lim

De La Salle University, 2401 Taft Ave., Manila, 1004 Philippines

March 19, 2014
May 5, 2014
Online released:
September 20, 2014
September 20, 2014
computer networked vision system, multiplecamera color-based object recognition, incremental tracking, real-time control, robot soccer system

This paper presents machine vision for locating and identifying 23 highly dynamic objects on 4.4 meters by 2.8 meters micro robot soccer playing field. The approach is based from the idea that the two camera vision subsystems should be synchronized and well informed in real time of the combined vision data and a selection of objects to track under each other’s camera view. A measure of effectiveness on using incremental tracking for two-camera operation is developed and is used to evaluate the introduced approach through experimentation. A real-time visualization of the whole playfield containing the 22 micro robots and a golf ball is also provided for the system operator to validate the objects’ actual poses with the vision system’s measurements. Results show that the proposed technique is very fast, accurate, reliable, and robust to external disturbances.

  1. [1] C. H. Messom, G. S. Gupta, and H. L. Sng, “Distributed Real-Time Image Processing for a Dual Camera System,” Proc. of CIRAS 2001, pp. 53-59, 2001.
  2. [2] H. Jiang, Q. Peng, H. A. Lee, E. L. CTeoh, and H. L. Sng, “Color Vision and Robot/Ball Identification for a Large Field Soccer Robot System,” Proc. of 2nd Int. Conf. Autonomous Robots and Agents, New Zealand, 2004.
  3. [3] D. Ball, G. Wyeth, and S. Nuske, “A Global Vision System for a Robot Soccer Team,” Proc. of 2004 Australasian Conf. Robotics and Automation, 2004.
  4. [4] J. C. Wolf, J. D. Oliver, P. Robinson, and C. Diot, “Multi-site Development of a FIRA large league robot football system,” Proc. of Int. Conf. Computational Intelligence, Robotics and Autonomous Systems (CIRAS 2005), 2005.
  5. [5] M. H. Koo, Y. K. Lee, K. H. Lee, T. H. Kim, J. K. Lee, and J. H. Kim, “Development of Robot Soccer System for 11-a-side MiroSot,” Proc. of 2004 FIRA Robot World Congress, 2004.
  6. [6] B. Li, E. Smith, H. Hu, and L. Spacek, “A Real-time Visual Tracking System in the Robot Soccer Domain,” Proc. of 2000 EUREL Robotics, 2000.
  7. [7] N. Weiss and L. Hildebrand, “An Exemplary Robot Soccer Vision System,” Proc. of CLAWAR/EURON Workshop on Robots in Entertainment, Leisure and Hobby, 2004.
  8. [8] M. Simon, S. Behnke, and R. Rojas, “Robust Real Time Color Tracking,” Proc. of 4th Int. Worshop on Robocup, pp. 62-71, 2000.
  9. [9] G. Bradski and A. Kaehler, “Learning OpenCV,” O’Reilly Media Inc., 2008.
  10. [10] N. Gunay and E. Dadios, “Multiple Robot Recognition In Real Time Using OpenCV,” Proc. of Int. Conf. Mechatronics Technology, 2009.
  11. [11] N. Gunay and E. Dadios, “An Efficient Method for Locating Highly Dynamic Objects in a Robot Soccer Environment,” To be included in the Proc. of the 5th HNICEM Int. Conf. (HNICEM 2011), 2011.
  12. [12] M. Veloso, M. Bowling, S. Achim, K. Han, and P. Stone, “The CMUnited-98 Champion Small Robot Team,” RoboCup-98: Robot Soccer World Cup II, Lecture Notes in Artificial Intelligence, pp. 77-92, Springer Verlag, 1999.
  13. [13] N. Gunay and E. Dadios, “A Robust and Accurate Color-Based Global Vision Recognition of Highly Dynamic Objects in Real Time,” To be included in the Proc. of the 8th Asian Control Conference (ASCC 2011), 2011.
  14. [14] N. Weiss, “Adaptive Supervision of Moving Objects for Mobile Robotics Application,” Journal of Robotics and Autonomous Systems, Vol.57, pp. 982-995, 2009.
  15. [15] FIRA Official Website,

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Mar. 27, 2017