Abstract
This paper presents low-cost system for counting canoes and canoeists to control cannoning tourist routes. The created system was implemented on Raspberry Pi 2 and the total cost of the tracking device is less than 200$. The proposed algorithm uses background subtraction and Support Vector Machines to track vessels and recognize canoes among them. The obtained results are rewarding as for low-cost solution. Depending on considered group of objects the accuracy of the algorithm reaches 84, 89.5, and 96 % for canoes, vessels, and all objects respectively.
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Acknowledgments
The project was carried out in cooperation with NFC Vision.
The research was partially supported by the National Science Center, grant No 2012/07/B/ST6/01501, decision no UMO–2012/07/B/ST6/01501.
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Wilkowski, A., Luckner, M. (2016). Low-Cost Canoe Counting System for Application in a Natural Environment. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Challenges in Automation, Robotics and Measurement Techniques. ICA 2016. Advances in Intelligent Systems and Computing, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-29357-8_61
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DOI: https://doi.org/10.1007/978-3-319-29357-8_61
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