Crowd Multi Prediction: Single Network for Crowd Counting, Localization and Anomaly Detection

Date

2023-01-01

Author

Coskun, Muhammet Furkan
Akar, Gözde

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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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Citation Formats

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.