Abstract
In this paper we present a simple and new algorithm that tracks the contour of several homogenous regions in a sequence of images. The method exploits the fact that, when i.e. observing a moving object (exposing a homogenous region), the regions in two consecutive frames often overlap. We show that the method is valuable for the RoboCup domain: It allows to track the green playing field and the goals very efficiently, to detect the white marking lines precisely, enabling us to recognize features in them (the center circle, the quatre circles, corners, the rectangle of the penalty area,...). It is also useful to find the ball and the obstacles. Furthermore, it provides data for path planning based on potential field methods without further computation. We compared the algorithm with the fastest existing method and measured a speed enhancement of 30 percent. In contrast to other methods, our algorithm not only tracks the center of blobs but yields the precise boundary shape of the objects as a set of point sequences. First tests with real world data have confirmed the applicability for other domains than RoboCup.
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Adams, R., Bischof, L.: Seeded region growing. IEEE Transactions on Pattern Analysis and Machine Intelligence 16(6), 641–647 (1994)
Doucet, N.G.A., de Freitas, N. (eds.): Sequential Monte Carlo Methods in Practice. In: Statistics for Engineering and Information Science, Springer, Heidelberg (2001) ISBN 0-387-95146-6
Blake, A., Isard, M.: Active Contours. Springer, Heidelberg (1998)
Brice, C.R., Fennema, C.L.: Scene analysis using regions. Artificial Intelligence 1, 205–226 (1970)
Bruce, J., Balch, T., Veloso, M.: Fast and inexpensive color image segmentation for interactive robots. In: Proceedings of IROS 2000, Japan (October 2000)
Canny, J.: A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 8, 679–698 (1986)
Cohen, L.D.: On active contour models and balloons. CVGIP:IU (1991)
Cook, G.W., Delp, E.J.: Multiresolution sequential edge linking. In: Proceedings of the IEEE International Conference on Image Processing, October 1995, pp. 41–44 (1995)
Hojjatoleslami, S.A., Kittler, J.: Region growing: a new approach. IEEE Transactions of Image Processing 7(7), 1079–1084 (1998)
Hough, P.V.C.: Method and means for recognizing complex patterns. US Patent 3,069,654 (December 1962)
Jonker, P., Caarls, J., Bokhove, W.: Fast and accurate robot vision for vision based motion. In: Stone, P., Balch, T., Kraetzschmar, G.K. (eds.) RoboCup 2000. LNCS (LNAI), vol. 2019, pp. 149–155. Springer, Heidelberg (2001)
Latombe, J.: Robot Motion Planning. Kluwer Academic Publishers, Dordrecht (1991) ISBN 0-7923-9206-X
Lindeberg, T.: Scale-Space Theory In Computer Vision. Kluwer Academic Publishers, Dordrecht (1994)
Lu, F., Milios, E.: Robot pose estimation in unknown environments by matching 2d range scans. In: CVPR 1994, pp. 935–938 (1994)
Mallat, S., Zhong, S.: Characterization of signals from multiscale edges. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 14(7), 710–732 (1992)
Mehrotra, R., Namudura, K.R., Ranganathan, N.: Gabor filter-based edge detection. Pattern Recognition 25, 1479–1494 (1992)
Pavlidis, T.: Integrating region growing and edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 12(3), 225–233 (1990)
Pingle, K.K.: Visual perception by computer. In: Grasselli, A. (ed.) Automatic Interpretation and Classification of Images, pp. 277–284. Academic Press, New York (1969)
Roberts, L.G.: Machine perception of three-dimensional solids. In: Tippet, J.T., et al. (eds.) Optical and Electro-Optical Information Processing, pp. 159–197. MIT Press, Cambridge (1965)
Ruzon, M.A., Tomasi, C.: Color edge detection with the compass operatro. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 160–166 (1999)
Siebert, A.: Dynamic region growing (1997)
Zucker, S.W.: Region growing: Childhood and adolescence. Computer Graphics and Image Processing 5, 382–399 (1976)
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von Hundelshausen, F., Rojas, R. (2004). Tracking Regions. 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_22
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DOI: https://doi.org/10.1007/978-3-540-25940-4_22
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