Abstract
The paper considers the issues of trajectory tracking of a large number of objects on video images in modes close to real time. To implement such support, a combination of algorithms based on the YOLO v3 convolutional neural network (CNN), doubly stochastic filters and pseudo-gradient procedures for aligning image fragments is proposed. The obtained numerical performance characteristics show the consistency of such a combination and the possibility of its application in real video processing systems.
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Acknowledgements
The reported study was funded by RFBR grants, Projects No. 19-29-09048 and No. 18-47-730009.
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Andriyanov, N., Dementiev, V., Kondratiev, D. (2021). Tracking of Objects in Video Sequences. In: Czarnowski, I., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 238. Springer, Singapore. https://doi.org/10.1007/978-981-16-2765-1_21
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DOI: https://doi.org/10.1007/978-981-16-2765-1_21
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