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Algorithm for tracking an object observed by а video camera

https://doi.org/10.29235/1561-8323-2024-68-2-105-111

Abstract

An algorithm for tracking an object observed on video frames is presented. The specific feature of the constructed algorithm is the automatic detection and capture of an object of one of predetermined types, its further reliable tracking, the rapid re-capture of the tracked object in the case of a failure of tracking, the capture of another object of desired type if the tracked object disappears. An object of interest on video frames is detected using a neural network detector, whereas tracking is performed by the developed algorithm.

About the Authors

B. A. Zalesky
United Institute of Informatics Problems of the National Academy of Sciences of Belarus
Belarus

Boris A. Zalesky– D. Sc. (Physics and Mathematics), Head of the Laboratory

6, Surganov Str., 220012, Minsk



V. A. Ivanyukovich
United Institute of Informatics Problems of the National Academy of Sciences of Belarus
Belarus

Vladimir A. Ivanyukovich– Junior Researcher

6, Surganov Str., 220012, Minsk



References

1. Object Tracking (2024). Available at: https://paperswithcode.com/task/object-tracking (accessed 05 January 2024).

2. Proceedings of Conference on Computer Vision and Pattern Recognition 2023. CVPR 2023. Vancouver Jun 18 2023. Available at: https://openaccess.thecvf.com/CVPR2023 (accessed 05 January 2024).

3. Chen F., Wang X., Zhao Y., Lv Sh., Niu X. Visual object tracking: A survey. Computer Vision and Image Understanding, 2022, vol. 222, art. 103508. https://doi.org/10.1016/j.cviu.2022.103508

4. Wojke N., Bewley A., Paulus D. Simple online and realtime tracking with a deep association metric. 2017 IEEE International Conference on Image Processing (ICIP), 17–20 September 2017, Beijing, China, 2017, pp. 3645–3649. https://doi.org/10.1109/ICIP.2017.8296962

5. Zhang Y., Sun P., Jiang Y., Yu D., Weng F., Yuan Z., Luo P., Liu W., Wang X. ByteTrack: Multi-Object Tracking by Associating Every Detection Box. Avidan S., Brostow G., Cissé M., Farinella G. M., Hassner T. (eds.). Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol. 13682. Springer, Cham, 2022, pp. 1–21. https://doi.org/10.1007/978-3-031-20047-2_1


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ISSN 1561-8323 (Print)
ISSN 2524-2431 (Online)