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Smoking Detection in Video

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  • P. Sumalatha
  • Gurram Soumya
  • Angaluri Yashaswini Tapathi

Abstract

This paper presents a novel approach for identifying smoking behavior using deep learning to extract important features from an image. The approach involves using deep learning to identify key regions in an image and a conditional detection system built using YOLOv5 to improve performance and simplify the model. The method was tested on a dataset containing 7,000 images with equal representation of smokers and non-smokers in various settings. The effectiveness of the technique was evaluated using both quantitative and qualitative measures, resulting in a classification accuracy of 96.74% on the dataset.

Suggested Citation

  • P. Sumalatha & Gurram Soumya & Angaluri Yashaswini Tapathi, 2023. "Smoking Detection in Video," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 9(3), pages 177-182, June.
    • Handle: RePEc:jbh:ijsrcs:v9:y2023:i3:id:hcseit2390339
    Note: Article URL: https://ijsrcseit.com/CSEIT2390339
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