A survey on deep learning-based real-time crowd anomaly detection for secure distributed video surveillance-Reference-Cited by-同舟云学术

A survey on deep learning-based real-time crowd anomaly detection for secure distributed video surveillance

Published:2021-06-25 Issue: Volume: Page:
ISSN:1617-4909
Container-title:Personal and Ubiquitous Computing
language:en
Short-container-title:Pers Ubiquit Comput

Author:

Rezaee Khosro^ORCID,Rezakhani Sara Mohammad,Khosravi Mohammad R.,Moghimi Mohammad Kazem

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,Computer Science Applications,Hardware and Architecture

Link

https://link.springer.com/content/pdf/10.1007/s00779-021-01586-5.pdf

Reference118 articles.

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2. Yuan Y, Fang J, Wang Q (2014) Online anomaly detection in crowd scenes via structure analysis. IEEE transactions on cybernetics 45(3):548–561

3. Singh K, Rajora S, Vishwakarma DK, Tripathi G, Kumar S, Walia GS (2020) Crowd anomaly detection using aggregation of ensembles of fine-tuned ConvNets. Neurocomputing. 371:188–198

4. Mousavi H, Mohammadi S, Perina A, Chellali R, Murino V (2015) Analyzing tracklets for the detection of abnormal crowd behavior. In 2015 IEEE Winter Conference on Applications of Computer Vision (pp. 148-155)

5. Hatirnaz E, Sah M, Direkoglu C (2020) A novel framework and concept-based semantic search interface for abnormal crowd behaviour analysis in surveillance videos. Multimed Tools Appl 20:1–39

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