Visualization system for fire detection in the video sequences

被引：0

作者：

Laptev N.V. ^{[1
]}

Laptev V.V. ^{[1
]}

Gerget O.M. ^{[1
]}

Kravchenko A.A. ^{[1
]}

Kolpashchikov D.Yu. ^{[1
]}

机构：

[1] National Research Tomsk Polytechnic University

来源：

Scientific Visualization | 2021年 / 13卷 / 02期

关键词：

Algorithm; Computer vision; Image visualization; Machine learning; Neural network; Object detection; Video analysis;

D O I：

10.26583/sv.13.2.01

中图分类号：

学科分类号：

摘要：

The paper deals with the analysis of the visual images obtained from fire detection systems. We review the existing approaches to the analysis of video surveillance data and propose a tool for data labeling and visualization. The proposed solution for visual image analysis is based on a neural network (object detection technology). Recognition of hazard locations was carried out using the EfficientDet-D1 model. Video pre- and post-processing algorithms were implemented to improve visual image classification. The pre-processing was used to generate a frame preserving the features of objects that dynamically change over time. The post-processing combines the results of sequential detection of characteristic features on each frame, in particular, features of a smoke cloud. The results of the system operation are presented: visual image classification accuracy was 81%, while localization accuracy was 87%. © 2021 National Research Nuclear University. All rights reserved.

引用

页码：1 / 9

页数：8

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