001     1003812
005     20230307201804.0
024 7 _ |a 2128/34078
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037 _ _ |a FZJ-2023-01262
041 _ _ |a English
100 1 _ |a Alia, Ahmed
|0 P:(DE-Juel1)185971
|b 0
|e Corresponding author
111 2 _ |a Conference for Research Software Engineering in Germany
|g deRSE23
|c Paderborn
|d 2023-02-20 - 2023-02-22
|w Germany
245 _ _ |a DL4PuDe: Deep-Learning Framework for Pushing Detection in Pedestrian Dynamics
260 _ _ |c 2023
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a Other
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336 7 _ |a INPROCEEDINGS
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336 7 _ |a LECTURE_SPEECH
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520 _ _ |a At crowded event entrances, some pedestrians start pushing others to gain faster access to the events, resulting in dangerous situations. Pushing identification in video recordings of events is crucial for understanding pushing dynamics, thereby managing entrances safely. This talk presents a deep-learning framework to help researchers automatically identify pushing in videos of crowds. The framework consists of four modules: (1) Optical Flow Estimator that uses a pre-trained optical flow model to estimate the dense displacement fields from input video. (2) Wheel Visualization for generating motion information maps from the displacement fields. (3) EfficientNet-B0 Classifier that aims to identify pushing behavior from the maps. (4) A False Reduction and Annotation module; to reduce the number of false identifications of the classifier, annotate the regions of pushing and output the annotated video. We used five real-world ground truth of pushing behavior videos for the evaluation. Experimental results show that the framework achieves 86% accuracy. The framework is open-source and available at https://github.com/PedestrianDynamics/DL4PuDe.
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
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536 _ _ |a Pilotprojekt zur Entwicklung eines palästinensisch-deutschen Forschungs- und Promotionsprogramms 'Palestinian-German Science Bridge' (01DH16027)
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700 1 _ |a Maree, Mohammed
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Chraibi, Mohcine
|0 P:(DE-Juel1)132077
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856 4 _ |u https://pad.gwdg.de/deRSE23-session-pads-ai-and-ml
856 4 _ |u https://juser.fz-juelich.de/record/1003812/files/Abstract-DL4PuDe.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/1003812/files/Alia-Ahmed-DL4PuDe.pdf
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909 C O |o oai:juser.fz-juelich.de:1003812
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910 1 _ |a Forschungszentrum Jülich
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913 1 _ |a DE-HGF
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|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
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914 1 _ |y 2023
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