Abstract
In order to achieve automatic prediction and warning of hazardous crowd behaviors, a Spatio-Temporal Volume (STV) analysis method is proposed in this research to detect crowd abnormality recorded in CCTV streams. The method starts from building STV models using video data. STV slices – called Spatio-Temporal Textures (STT) - can then be analyzed to detect crowded regions. After calculating the Gray Level Co-occurrence Matrix (GLCM) among those regions, abnormal crowd behavior can be identified, including panic behaviors and other behavioral patterns. In this research, the proposed STT signatures have been defined and experimented on benchmarking video databases. The proposed algorithm has shown a promising accuracy and efficiency for detecting crowd-based abnormal behaviors. It has been proved that the STT signatures are suitable descriptors for detecting certain crowd events, which provide an encouraging direction for real-time surveillance and video retrieval applications.
Original language | English |
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Title of host publication | Proceedings of the 23rd International Conference on Automation & Computing, (University of Huddersfield, 7-8 September 2017) |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Number of pages | 5 |
ISBN (Electronic) | 9780701702601 |
ISBN (Print) | 9781509050406 |
DOIs | |
Publication status | Published - 26 Oct 2017 |
Event | 23rd International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing - University of Huddersfield, Huddersfield, United Kingdom Duration: 7 Sep 2017 → 8 Sep 2017 Conference number: 23 https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=41042 (Link to Conference Website) |
Conference
Conference | 23rd International Conference on Automation and Computing |
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Abbreviated title | ICAC 2017 |
Country/Territory | United Kingdom |
City | Huddersfield |
Period | 7/09/17 → 8/09/17 |
Other | The scope of the conference covers a broad spectrum of areas with multi-disciplinary interests in the fields of automation, control engineering, computing and information systems, ranging from fundamental research to real-world applications. |
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