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Output details

13 - Electrical and Electronic Engineering, Metallurgy and Materials

Queen Mary University of London : A - Electrical and Electronic engineering

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Output 3 of 60 in the submission

Article title

A Probabilistic Approach for Vision-Based Fire Detection in Videos

Type

D - Journal article

DOI

10.1109/TCSVT.2010.2045813

Title of journal

IEEE Transactions on Circuits and Systems for Video Technology

Article number

Volume number

Issue number

First page of article

721

ISSN of journal

1558-2205

Year of publication

2010

URL

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5430942

Number of additional authors

Additional information

Introduced one of the first techniques for automated video-based fire detection. Work led to cooperation in the security field with United Technologies, (UTRC): http://www.utrc.utc.com/pages/our_company.html. Ongoing cooperation resulted in recent (2011) grant from the EU 'SecurityDG' (http://cordis.europa.eu/fp7/security/home_en.html); grant value, €0.7M QMUL and €0.9M for UTRC (Lasie project start date 01.01.2014). The technology was also key to securing four large cooperative projects bringing additional €3.2M funding for QMUL: K-Space, RUSHES, MESH and aceMedia (Prof. K.V Rijsbergen: keith@dcs.gla.ac.uk, Dr. Peter Houghton: PDHoughton@taz.dstl.gov.uk). This well cited seminal paper also led to a series of four additional papers published by the author in IEEE transactions.

Interdisciplinary

Cross-referral requested

Research group

None

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract