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Early Wildfire Detection Using Convolutional Neural Network

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Frontiers of Computer Vision (IW-FCV 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1212))

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Abstract

Wildfires are one of the disasters that are difficult to detect early and cause significant damage to human life, ecological systems, and infrastructure. There have been several research attempts to detect wildfires based on convolutional neural networks (CNNs) in video surveillance systems. However, most of these methods only focus on flame detection, thus they are still not sufficient to prevent loss of life and reduce economic and material damage. To tackle this issue, we present a deep learning-based method for detecting wildfires at an early stage by identifying flames and smokes at once. To realize the proposed idea, a large dataset for wildfire is acquired from the web. A light-weight yet powerful architecture is adopted to balance efficiency and accuracy. And focal loss is utilized to deal with the imbalance issue between classes. Experimental results demonstrate the effectiveness of the proposed method and validate its suitability for early wildfire detection in a video surveillance system.

This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by Korea government (MSIT) (No. 2019-0-00203, Development of Predictive Visual Security Technology for Preemptive Threat Response).

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Authors and Affiliations

  1. Electronics and Telecommunications Research Institute, Daejon, Republic of Korea

    Seon Ho Oh, Sang Won Ghyme & Geon-Woo Kim

  2. School of Computer Science and Engineering, Kyungpook National University, Daegu, Republic of Korea

    Soon Ki Jung

Authors
  1. Seon Ho Oh
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  2. Sang Won Ghyme
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  3. Soon Ki Jung
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  4. Geon-Woo Kim
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Corresponding author

Correspondence to Geon-Woo Kim .

Editor information

Editors and Affiliations

  1. Saitama Institute of Technology, Saitama, Japan

    Wataru Ohyama

  2. Kyungpook National University, Daegu, Korea (Republic of)

    Soon Ki Jung

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Oh, S.H., Ghyme, S.W., Jung, S.K., Kim, GW. (2020). Early Wildfire Detection Using Convolutional Neural Network. In: Ohyama, W., Jung, S. (eds) Frontiers of Computer Vision. IW-FCV 2020. Communications in Computer and Information Science, vol 1212. Springer, Singapore. https://doi.org/10.1007/978-981-15-4818-5_2

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  • DOI: https://doi.org/10.1007/978-981-15-4818-5_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4817-8

  • Online ISBN: 978-981-15-4818-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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