CALCULATION OF GPS COORDINATES OF OBJECTS DETECTED FROM AERIAL PHOTOGRAPHY
https://doi.org/10.26583/vestnik.2023.249
Abstract
This article discusses an algorithm that allows you to calculate the GPS coordinates of an object detected in images taken from an unmanned aerial vehicle (quadcopter). The developed algorithm can be used in the tasks of detecting various objects and then plotting their coordinates on maps. The authors of the article describe an approach to solving this problem, identify the main stages of the algorithm. An approach to writing a program implemented in the C++ programming language using the OpenCV open source library (machine vision library) is described. The results of the program are demonstrated. The authors managed to achieve the accuracy of calculating the GPS coordinates of objects of the order of one meter, which is comparable to the accuracy of satellite positioning of a quadcopter from which aerial photography of the underlying surface is carried out.
About the Authors
G. S. FinyakinRussian Federation
V. B. Chemodanov
Russian Federation
A. A. Shatsky
Russian Federation
References
1. Kruglov V.V., Borisov V.V. Iskustvennie neyronnie sety. Teoriya i praktika [Artificial neural networks. Theory and practice]. Moscow, Goryachaya liniya-Telecom Publ., 2002. 382 p.
2. Hadsell R., Chopra S., LeCun Y. Dimensionality reduction by learning an invariant mapping [electronic recource]. Aviable at: http://yann.lecun.com/ exdb/publis/pdf/hadsell-cho-pra-lecun-06.pdf (accessed 29.01.2023).
3. Vorontsov K.V. Neyronnie sety, videokurs [neural networks, video course: electronic recource]. Aviable at: https://www.youtube.com/watch?v= WjwA5DqxL-c (accessed 29.01.2023).
4. Li F.F., Johnson J., Yeung S. Convolutional neural networks [electronic recource]. Aviable at: http://cs231n.stanford.edu/syllabus.html (accessed 29.01.2023).
5. Bochkovskiy A. and Chien-Yao Wang, Hong-Yuan Mark Liao. Optimal speed and accuracy of object detection [electronic recource]. Aviable at: https://arxiv.org /pdf/2004.10934.pdf (accessed 29.01.2023).
6. Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark. Scaling cross stage partial network. Proceedings of the IEEE/CVF «Conference on Computer Vision and Pattern Recognition (CVPR)», 2021. P. 13029.
7. Shatskit A.A., Evgeniev I.Yu. Neural network astronomy as a new tool for observing bright and compact objects. Journal of Experimental and Theoretical Physics. 2019. Vol. 128. P. 592–598.
8. Baer R. Linear algebra and projective geometry. Dover Publications, Publ. 2005. 336 p.
9. Hodarev. Obrabotka i analyz tsifrovih izobrajeniy s primeramy na LabVIEW y IMAQ Vision / Yu.Yu. Vizilter, S.Yu. Jeltov, V.A., Knyaz A.H. [Processing and analysis of digital images with examples on LabVIEW and IMAQ Vision]. M.: DMK Press, Publ., 2007. 464 p.
10. Korn G., Korn T. Spravochnik po matematike [handbook of mathematics]. M.: Nauka Publ., 1973. 832 p.
Review
For citations:
Finyakin G.S., Chemodanov V.B., Shatsky A.A. CALCULATION OF GPS COORDINATES OF OBJECTS DETECTED FROM AERIAL PHOTOGRAPHY. Vestnik natsional'nogo issledovatel'skogo yadernogo universiteta "MIFI". 2023;12(1):20-27. (In Russ.) https://doi.org/10.26583/vestnik.2023.249