This paper has proposed a novel approach to classify the subjects' smoking behavior by extracting relevant regions from a given image using deep learning. After the classification, we have proposed a conditional detection module based on Yolo-v3, which improves model's performance and reduces its complexity. As per the best of our knowledge, we are the first to work on this dataset. This dataset contains a total of 2,400 images that include smokers and non-smokers equally in various environmental settings. We have evaluated the proposed approach's performance using quantitative and qualitative measures, which confirms its effectiveness in challenging situations. The proposed approach has achieved a classification accuracy of 96.74% on this dataset.
@article{arxiv.2103.12523,
title = {Region extraction based approach for cigarette usage classification using deep learning},
author = {Anshul Pundhir and Deepak Verma and Puneet Kumar and Balasubramanian Raman},
journal= {arXiv preprint arXiv:2103.12523},
year = {2021}
}
Comments
5 pages, 16 figures. To appear in the proceedings of the 28th IEEE International Conference on Image Processing (IEEE - ICIP), September 19-22, 2021, Anchorage, Alaska, USA