https://libeldoc.bsuir.by/handle/123456789/54444
Title: | Crowd motion detection in video by combining CNN and integral optical flow |
Authors: | Huafeng Chen Pashkevich, A. Bohush, R. Ablameyko, S. |
Keywords: | материалы конференций;optical flow;crowd motion analysis;video surveillance |
Issue Date: | 2023 |
Publisher: | BSU |
Citation: | Crowd motion detection in video by combining CNN and integral optical flow / Huafeng Chen [et al.] // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 219–222. |
Abstract: | The paper proposes a new approach for crowd motion detection in video by combining CNN and integral optical flow. At first, definitions of crowd motion are given, along with motion parameters that can be used to perform crowd analysis. Secondly, crowd motion features and parameters are defined. Thirdly, an algorithm of crowd behavior analysis using CNN and integral optical flow is proposed. Experimental results show that, with the help of CNN, optical flow can be calculated more accurately and quickly, and by using integral optical flow, the algorithm demonstrates stronger robustness to noise and the ability to get more accurate boundaries of moving objects. |
URI: | https://libeldoc.bsuir.by/handle/123456789/54444 |
Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) |
File | Description | Size | Format | |
---|---|---|---|---|
Huafeng_Chen_Crowd.pdf | 684.49 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.