Real-Time Fire Detection for Video-Surveillance Applications Using a Combination of Experts Based on Color, Shape, and Motion
Abstract
In this paper, we propose a method that is able to detect fires by analyzing videos acquired by surveillance cameras. Two main novelties have been introduced. First, complementary information, based on color, shape variation, and motion analysis, is combined by a multiexpert system. The main advantage deriving from this approach lies in the fact that the overall performance of the system significantly increases with a relatively small effort made by the designer. Second, a novel descriptor based on a bag-of-words approach has been proposed for representing motion. The proposed method has been tested on a very large dataset of fire videos acquired both in real environments and from the web. The obtained results confirm a consistent reduction in the number of false positives, without paying in terms of accuracy or renouncing the possibility to run the system on embedded platforms.
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Flames can be recognized by analyzing color, shape changes, and movement captured by camera.
“Flames can be recognized by analyzing the color, shape changes, and movement that are captured by the camera [131].”
From A Survey of Video Surveillance Systems in Smart City (2023) · cites this paper as [131]
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“Flames can be recognized by analyzing the color, shape changes, and movement that are captured by the camera [131].”
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Wu, H., Hu, Y., Wang, W., Mei, X., & Xian, J. (2022) · Sensors · doi:10.3390/s22197420 · Cited by 63 · see citing works
- Authors
- Foggia, P., Saggese, A., & Vento, M.
- Affiliations
- University of Salerno (IT)
- Venue
- IEEE Transactions on Circuits and Systems for Video Technology
- Published
- 2015-09
- Volume
- 25
- Issue
- 9
- Pages
- 1545-1556
- ISSN
- 1051-8215 (ISSN-L)
- 1558-2205
- OpenAlex
- W1996199746
- Cited by
- 483
- References
- 35
- Citations by year
- 2026: 40 · 2025: 57 · 2024: 65 · 2023: 102 · 2022: 73 · 2021: 48 · 2020: 37 · 2019: 30 · 2018: 10 · 2017: 11 · 2016: 8 · 2015: 2
- FWCI
- 24.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Circuits and Systems for Video Technology (publishedVersion)
- Funders
- A.I.Tech s.r.l. (), Fisciano, Italy
- Topics
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Fire Detection and Safety Systems
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Fire dynamics and safety research
- Keywords
- fire detection, video surveillance, color analysis, shape analysis, motion analysis, false positive reduction, embedded platform, real-time detection
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