Abstract
Tracking of multiple objects belongs to one of the fundamental tasks of computer vision. In this paper an improvement to the continuously adaptive mean shift tracking method is proposed. It consists in substitution of the probabilistic density function for the especially formed membership function. This makes possible design of tracking systems in terms of fuzzy logic. Additionally, a special data structure was developed to allow tracking of multiple objects at a time. It stores information on image regions which are active for tracking. By this it provides initial conditions for tracking in subsequent frames which also speeds up computations. The method was used and verified in an application of the road signs tracking in real time of 30 frames/s.
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Cyganek, B. (2008). Real-Time Road Signs Tracking with the Fuzzy Continuously Adaptive Mean Shift Algorithm. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_22
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DOI: https://doi.org/10.1007/978-3-540-69731-2_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69572-1
Online ISBN: 978-3-540-69731-2
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