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Crowd Multi Prediction: Single Network for Crowd Counting, Localization and Anomaly Detection
Date
2023-01-01
Author
Coskun, Muhammet Furkan
Akar, Gözde
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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In this study, we propose a neural network to solve crowd counting, localization and abnormal event detection problems together. Our proposed model combines P2P-Net with a novel crowd anomaly detection module. The final network has a single backbone and multiple head structure. Synthetic datasets are used for training and evaluation. Results show that our model gets high accuracy in crowd anomaly detection task.
Subject Keywords
crowd analysis
,
crowd counting localization and abnormal event detection
,
multi-task prediction
,
synthetic crowd dataset generation with GTA-V game
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85149142426&origin=inward
https://hdl.handle.net/11511/102646
DOI
https://doi.org/10.1109/icce56470.2023.10043501
Conference Name
2023 IEEE International Conference on Consumer Electronics, ICCE 2023
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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BibTeX
M. F. Coskun and G. Akar, “Crowd Multi Prediction: Single Network for Crowd Counting, Localization and Anomaly Detection,” Nevada, Amerika Birleşik Devletleri, 2023, vol. 2023-January, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85149142426&origin=inward.