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<p>This paper provides a suspicious activity detection framework in road traffic based on aerial surveillance video, which combines Kd-SLIC-K-means clustering and SBAF-CNN. The suggested technique will be used to improve object segmentation and classification to give better detection results. The aerial traffic datasets are experimentally evaluated and the model has an accuracy of 98.97, which is better than the current methods. The findings show that the suggested approach can help to detect suspicious patterns in traffic situations. Nevertheless, the model has been tested under certain conditions and additional tests on large scale and diverse data sets are needed to establish its generalizability in real world scenarios.</p>

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Suspicious detection in road traffic based on Kd-SLIC-K-means and SBAF-CNN using aerial view surveillance video

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月5日

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  • Raj Kumar Patra,
  • Saurabh Bhattacharya,
  • Md Rashid Mahmood,
  • Naresh Kumar Kar,
  • Parul Dubey,
  • Rohit Raja,
  • Sonu Agrawal

摘要

This paper provides a suspicious activity detection framework in road traffic based on aerial surveillance video, which combines Kd-SLIC-K-means clustering and SBAF-CNN. The suggested technique will be used to improve object segmentation and classification to give better detection results. The aerial traffic datasets are experimentally evaluated and the model has an accuracy of 98.97, which is better than the current methods. The findings show that the suggested approach can help to detect suspicious patterns in traffic situations. Nevertheless, the model has been tested under certain conditions and additional tests on large scale and diverse data sets are needed to establish its generalizability in real world scenarios.