Abstract
This paper addresses the problem of estimating the location and size of a wildfire, within the frame of a semi-autonomous recon and data analytics quadcopter. We approach this problem by developing three different algorithms, in order to accommodate this problem. Two of these taking into the account that the middle of the camera’s FOV is horizontal with respect to the drone it is mounted. The third algorithm relates to the bottom point of the FOV, directly under the drone in 3D space. The evaluation shows that having the pixels correlate to ratios in percentages rather than predetermined values, with respect to the edges of the fire, will result in better performance and higher accuracy. Placing the monocular camera horizontally in relation to the drone will provide an accuracy of 68.20%, while mounting the camera with an angle, will deliver an accuracy of 60.76%.
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de Paula, L.G., Hyttel, K., Geipel, K.R., de Domingo Gil, J.E., Novac, I., Chrysostomou, D. (2019). Estimation of Wildfire Size and Location Using a Monocular Camera on a Semi-autonomous Quadcopter. In: Tzovaras, D., Giakoumis, D., Vincze, M., Argyros, A. (eds) Computer Vision Systems. ICVS 2019. Lecture Notes in Computer Science(), vol 11754. Springer, Cham. https://doi.org/10.1007/978-3-030-34995-0_13
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DOI: https://doi.org/10.1007/978-3-030-34995-0_13
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