Aerial Ball Perception Based on the Use of a Single Perspective Camera

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• 作者：Jo?o Silva ; Mário Antunes ; Nuno Lau ; António J. R. Neves ; Luís Seabra Lopes
• 刊名：Lecture Notes in Computer Science
• 出版年：2013
• 出版时间：2013
• 年：2013
• 卷：8154
• 期：1
• 页码：247-258
• 全文大小：677KB
• 参考文献：1. Voigtlrande, A., Lange, S., Lauer, M., Riedmiller, M.: Real-time 3D ball recognition using perspective and catadioptric cameras. In: Proc. of the 3rd European Conference on Mobile Robots, Freiburg, Germany (2007)
  2. Burla, A.: 3D ball detection in robocup. Master’s thesis, University of Stuttgart (2007)
  3. Mitri, S., Frintrop, S., Pervolz, K., Surmann, H., Nuchter, A.: Robust object detection at regions of interest with an application in ball recognition. In: Proc. of the 2005 IEEE International Conference on Robotics and Automation, ICRA 2005, Barcelona, Spain, pp. 125-30 (2005)
  4. Hanek, R., Schmitt, T., Buck, S.: Fast image-based object localization in natural scenes. In: Proc. of the 2002 IEEE/RSJ Int. Conference on Intelligent Robotics and Systems, Lausanne, Switzerland, pp. 116-22 (2002)
  5. Treptow, A., Zell, A.: Real-time object tracking for soccer-robots without color information. Robotics and Autonomous Systems?48, 41-8 (2004) CrossRef
  6. Mitri, S., Pervolz, K., Surmann, H., Nuchter, A.: Fast color independent ball detection for mobile robots. In: Proc. of the 2004 IEEE Int. Conference on Mechatronics and Robotics, Aachen, Germany, pp. 900-05 (2004)
  7. Lu, H., Zheng, Z., Liu, F., Wang, X.: A robust object recognition method for soccer robots. In: Proc. of the 7th World Congress on Intelligent Control and Automation, Chongqing, China (2008)
  8. Neves, A.J.R., Azevedo, J.L., Cunha, B., Lau, N., Silva, J., Santos, F., Corrente, G., Martins, D.A., Figueiredo, N., Pereira, A., Almeida, L., Lopes, L.S., Pinho, A.J., Rodrigues, J., Pedreiras, P.: CAMBADA soccer team: from robot architecture to multiagent coordination. In: Papic, V. (ed.) Robot Soccer, pp. 19-5. INTECH (2010)
  9. Neves, A.J., Pinho, A.J., Martins, D.A., Cunha, B.: An efficient omnidirectional vision system for soccer robots: From calibration to object detection. Mechatronics?21, 399-10 (2011) mechatronics.2010.05.006">CrossRef
  10. Pereira, R., Lopes, L.S.: Learning visual object categories with global descriptors and local features. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (eds.) EPIA 2009. LNCS, vol.?5816, pp. 225-36. Springer, Heidelberg (2009) CrossRef
  11. Antunes, M.L.P.: Semantic vision agent for robotics. Master’s thesis, University of Aveiro (2011)
  12. Silva, J., Lau, N., Neves, A.J.R., Rodrigues, J., Azevedo, J.L.: World modeling on an MSL robotic soccer team. Mechatronics?21, 411-22 (2011) mechatronics.2010.05.011">CrossRef
  
• 作者单位：Jo?o Silva (22)
  Mário Antunes (22)
  Nuno Lau (22)
  António J. R. Neves (22)
  Luís Seabra Lopes (22)
  
  22. IEETA / Department of Electronics, Telecommunications and Informatics, University of Aveiro, Portugal
  
• ISSN：1611-3349

文摘

The detection of the ball when it is not on the ground is an important research line within the Middle Size League of RoboCup. A correct detection of airborne balls is particularly important for goal keepers, since shots to goal are usually made that way. To tackle this problem on the CAMBADA team , we installed a perspective camera on the robot. This paper presents an analysis of the scenario and assumptions about the use of a single perspective camera for the purpose of 3D ball perception. The algorithm is based on physical properties of the perspective vision system and an heuristic that relates the size and position of the ball detected in the image and its position in the space relative to the camera. Regarding the ball detection, we attempt an approach based on a hybrid process of color segmentation to select regions of interest and statistical analysis of a global shape context histogram. This analysis attempts to classify the candidates as round or not round. Preliminary results are presented regarding the ball detection approach that confirms its effectiveness in uncontrolled environments. Moreover, experimental results are also presented for the ball position estimation and a sensor fusion proposal is described to merge the information of the ball into the worldstate of the robot.