Abnormal Crowd Behaviour Recognition in Surveillance Videos (CROSBI ID 684858)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Matković, Franjo ; Marčetić, Darijan ; Ribarić, Slobodan
engleski
Abnormal Crowd Behaviour Recognition in Surveillance Videos
The paper presents an approach to crowd behaviour recognition in surveillance videos. The approach is based on a 4-stage pipelined multi-person tracker adapted to microscopic crowd level representation and crowd behaviour recognition by the evaluation of fuzzy logic functions. The multiperson tracker combines a CNN-based detector and an optical flow-based tracker. The following tracker features are used: optical flow and histogram of optical flow orientation at the macroscopic level, and the tracklets and trajectories of a person and/or group of people at the microscopic level. The human interpretation of video sequences (real and/or video sequences obtained by simulators of crowds) is mapped into fuzzy logic predicates and fuzzy functions. Fuzzy logic predicates specify crowd motion patterns at the microscopic level for a person and/or group of people. They are building blocks of fuzzy logic functions which describe different scenarios of characteristic crowd behaviour. The preliminary results of three experiments for a runaway scenario show that the approach supports efficient and robust crowd behaviour recognition in surveillance videos.
Multi-person tracker, Crowd, Crowd behaviour recognition, Motion patterns, Fuzzy logic
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Podaci o prilogu
428-435.
2019.
objavljeno
10.1109/SITIS.2019.00075
Podaci o matičnoj publikaciji
2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
Yetongnon, Kokou
Los Alamitos (CA): Institute of Electrical and Electronics Engineers (IEEE)
978-1-7281-5686-6
Podaci o skupu
15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2019 )
predavanje
26.11.2019-29.11.2019
Napulj, Italija; Sorrento, Italija