Crowd detection and tracking in surveillance video sequences
The importance for video-based monitoring systems is on the rise leading to the growth of interest in the field of computer vision. With the increase of human population, crowd needs to be monitored, be it in a public place or in a building. Human monitoring can be quite tiresome and expensive,...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IEEE
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/80382/ http://irep.iium.edu.my/80382/1/80382%20Crowd%20Detection%20and%20Tracking%20in%20Surveillance%20Video.pdf http://irep.iium.edu.my/80382/2/80382%20Crowd%20Detection%20and%20Tracking%20in%20Surveillance%20Video%20SCOPUS.pdf |
| _version_ | 1848788946999312384 |
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| author | Salim, Sohail Khalifa, Othman Omran Abdul Rahman, Farah Lajis, Adidah |
| author_facet | Salim, Sohail Khalifa, Othman Omran Abdul Rahman, Farah Lajis, Adidah |
| author_sort | Salim, Sohail |
| building | IIUM Repository |
| collection | Online Access |
| description | The importance for video-based monitoring
systems is on the rise leading to the growth of interest in the field
of computer vision. With the increase of human population,
crowd needs to be monitored, be it in a public place or in a
building. Human monitoring can be quite tiresome and
expensive, making way for the upcoming of automated crowd
monitoring systems. Crowd analysis comprises of detection,
tracking, behavioral analysis, etc. In this paper a framework for
the detection of crowd, tracking and counting is proposed. The
goal is to create a robust system with utmost accuracy in its
results. Contrasted with sensor-based arrangements and humanbased, the video-based ones take into account more adaptable
functionalities, enhanced execution with lower costs. In this work,
the dataset PETS2009 was used. The results showed that the
proposed system has the capability to count all the people passing
through the field of view of the surveillance camera. The system
was tested for different types of crowd and the average efficiency
of various scenarios is 83.14%. |
| first_indexed | 2025-11-14T17:48:55Z |
| format | Proceeding Paper |
| id | iium-80382 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:48:55Z |
| publishDate | 2019 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-803822020-07-10T03:23:39Z http://irep.iium.edu.my/80382/ Crowd detection and tracking in surveillance video sequences Salim, Sohail Khalifa, Othman Omran Abdul Rahman, Farah Lajis, Adidah T Technology (General) The importance for video-based monitoring systems is on the rise leading to the growth of interest in the field of computer vision. With the increase of human population, crowd needs to be monitored, be it in a public place or in a building. Human monitoring can be quite tiresome and expensive, making way for the upcoming of automated crowd monitoring systems. Crowd analysis comprises of detection, tracking, behavioral analysis, etc. In this paper a framework for the detection of crowd, tracking and counting is proposed. The goal is to create a robust system with utmost accuracy in its results. Contrasted with sensor-based arrangements and humanbased, the video-based ones take into account more adaptable functionalities, enhanced execution with lower costs. In this work, the dataset PETS2009 was used. The results showed that the proposed system has the capability to count all the people passing through the field of view of the surveillance camera. The system was tested for different types of crowd and the average efficiency of various scenarios is 83.14%. IEEE 2019-04-06 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/80382/1/80382%20Crowd%20Detection%20and%20Tracking%20in%20Surveillance%20Video.pdf application/pdf en http://irep.iium.edu.my/80382/2/80382%20Crowd%20Detection%20and%20Tracking%20in%20Surveillance%20Video%20SCOPUS.pdf Salim, Sohail and Khalifa, Othman Omran and Abdul Rahman, Farah and Lajis, Adidah (2019) Crowd detection and tracking in surveillance video sequences. In: 2019 IEEE 6th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA 2019), 27 - 29 Aug 2019, Kuala Lumpur, Malaysia. https://ieeexplore.ieee.org/document/9057300 10.1109/ICSIMA47653.2019.9057300 |
| spellingShingle | T Technology (General) Salim, Sohail Khalifa, Othman Omran Abdul Rahman, Farah Lajis, Adidah Crowd detection and tracking in surveillance video sequences |
| title | Crowd detection and tracking in surveillance video sequences |
| title_full | Crowd detection and tracking in surveillance video sequences |
| title_fullStr | Crowd detection and tracking in surveillance video sequences |
| title_full_unstemmed | Crowd detection and tracking in surveillance video sequences |
| title_short | Crowd detection and tracking in surveillance video sequences |
| title_sort | crowd detection and tracking in surveillance video sequences |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/80382/ http://irep.iium.edu.my/80382/ http://irep.iium.edu.my/80382/ http://irep.iium.edu.my/80382/1/80382%20Crowd%20Detection%20and%20Tracking%20in%20Surveillance%20Video.pdf http://irep.iium.edu.my/80382/2/80382%20Crowd%20Detection%20and%20Tracking%20in%20Surveillance%20Video%20SCOPUS.pdf |