Abstract
Colour labeling is critical to the real-time performance of colour-based vision systems and is used for low-level vision by most RoboCup 2002 physically based teams. Unfortunately, colour labeling is sensitive to changes in illumination and manual calibration is both time consuming and error prone.
In this paper, we present KADC, a robust method for Knowledge-based Autonomous Dynamic Colour Calibration. By utilising the known geometry of the environment, landmarks are identified independent of colour classifications. Colour information from these landmarks is used to construct colour clusters of arbitrary shape. Clusters are dynamically updated through actions and by the use of a similarity metric, the Earth Mover’s Distance (EMD). We apply KADC to the RoboCup Legged League, generating a colourtable purely from geometrical knowledge of the environment and dynamically update this colortable to compensate for non-uniform changes in lighting conditions.
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Bruce, J., Balch, T., Veloso, M.: Fast and inexpensive color image segmentation for interactive robots. In: Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000), vol. 3, pp. 2061–2066 (2000)
Oda, K., Kato, T., Ishimura, T., Katsumi, Y.: The kyushu united team in the four legged robot league. In: Proceedings of RoboCup 2002, The 2002 International RoboCup Symposium (2002) (in Press)
Akm, H.L., Pavlova, P., Yildiz, O.T.: Ceberus 2002. In: Proceedings of RoboCup 2002, The 2002 International RoboCup Symposium (2002) (in Press)
Cayouette, F., Sud, D., Patel, K., Sarikaya, D., Cooperstock, J.: Mcgill reddogs 2002 team description report. In: Proceedings of RoboCup 2002, The 2002 International RoboCup Symposium (2002) (in Press)
Austermeier, H., Hartmann, G., Hilker, R.: Color-calibration of a robot vision system using self-organizing feature maps. In: Vorbrüggen, J.C., von Seelen, W., Sendhoff, B. (eds.) ICANN 1996. LNCS, vol. 1112, pp. 257–262. Springer, Heidelberg (1996)
Legenstein, D., Vincze, M., Chroust, S.: Finding colored objects under different illumination conditions in robotic applications. In: Proceedings of SPIE. Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, vol. 4197 (2000)
Mayer, G., Utz, H., Kraetzschmar, G.K.: Towards autonomous vision selfcalibration for soccer robots. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 214–219 (2002)
Rubner, Y., Tomasi, C., Guibas, L.: A metric for distributions with applications to image databases. In: IEEE International Conference on Computer Vision, pp. 59–66 (1998)
Elfes, A.: Occupancy grids: a stochastic spatial representation for active robot perception. In: Proceedings of the Sixth Conference of Uncertainty in AI, pp. 60–70 (1990)
Akm, H.L., Pavlova, P., Yildiz, O.T.: Ceberus 2002. In: Proceedings of RoboCup 2002, The 2002 International RoboCup Symposium (2002) (in Press)
Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Analysis and Machine Intelligence PAMI-8(6), 679–698 (1986)
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Cameron, D., Barnes, N. (2004). Knowledge-Based Autonomous Dynamic Colour Calibration. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds) RoboCup 2003: Robot Soccer World Cup VII. RoboCup 2003. Lecture Notes in Computer Science(), vol 3020. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25940-4_20
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DOI: https://doi.org/10.1007/978-3-540-25940-4_20
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