Abstract
The article is devoted to the problem of moving object detection on a video stream. One of the most important problems in this case is unstable background with moving elements that leads to increasing the level of misoperations while selecting moving objects on the scenes with background objects that change with the speed comparable with the speed of movement of object of interest through the image. Two types of dynamic background elements are considered: moving clouds and waving trees. Well known algorithms based on Gaussian mixture model, interest points detection approach (FAST, Harris, MinEigen and SURF) and optical flow (Farneback, Horne-Shunk and Lukas-Kanade) approaches are examined. Farneback based optical flow method is the most appropriate for this task. The new image series processing method is proposed in the paper and tested on the same examples with the background formed with moving clouds and waving trees. The results allow to conclude that it is good in case of moving clouds but its drawback is false detection in areas of waving trees. Future work requires a more advanced prediction model that can consider complicated trajectories of background fragments movement. #CSOC1120.
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Teplitskiy, E., Mitrokhin, M., Zakharov, S., Kuzmin, A., Mitrokhina, N., Sazykina, V. (2021). Video Processing Method for Moving Objects Detection on Scenes with Complex Dynamic Background. In: Silhavy, R. (eds) Informatics and Cybernetics in Intelligent Systems. CSOC 2021. Lecture Notes in Networks and Systems, vol 228. Springer, Cham. https://doi.org/10.1007/978-3-030-77448-6_33
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