A fire detection and localisation method based on keyframes and superpixels for large-space buildings. (12th January 2023)

• Record Type: Journal Article
• Authors: Fang, Qiansheng; Peng, Zhuang; Yan, Pu; Huang, Jing
• Is Part Of: International journal of intelligent information and database systems. Volume 16:Number 1(2023)
• Page Start: 1
• Page End: 19
• Publication Date: 2023-01-12
• Subjects: fire detection -- SuperPoint -- keyframes -- superpixels -- multi-feature -- fire localisation; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

Relevant fire detection and localisation methods suffer from the problems of slow detection speeds, low detection accuracies and low localisation precisions when applied to large-space buildings. To address these problems, a fire detection and localisation method based on keyframes and superpixels is proposed herein. Initially, we improve the SuperPoint method to extract video keyframes; then, we detect and locate fires only on these extracted video keyframes, thus extensively improving the detection speed. Then, we perform fire detection and localisation via superpixel and multi-feature fusion methods applied to the extracted video keyframes, and the results are more accurate than those obtained with single features, thus realising precise localisation. The experimental results obtained using a publicly available fire dataset reveal that our method realises good keyframe extraction, fire detection and fire localisation performances and is thus suitable for detecting and localising fires under large-building surveillance.