CFP last date
20 June 2025
Reseach Article

Deep Learning-based Person Tracking: A Smart Approach to Security and Civic Monitoring

by Shailendra Singh Kathait, Ashish Kumar, Samay Sawal, Ram Patidar, Khushi Agrawal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 4
Year of Publication: 2025
Authors: Shailendra Singh Kathait, Ashish Kumar, Samay Sawal, Ram Patidar, Khushi Agrawal
10.5120/ijca2025924797

Shailendra Singh Kathait, Ashish Kumar, Samay Sawal, Ram Patidar, Khushi Agrawal . Deep Learning-based Person Tracking: A Smart Approach to Security and Civic Monitoring. International Journal of Computer Applications. 187, 4 ( May 2025), 1-4. DOI=10.5120/ijca2025924797

@article{ 10.5120/ijca2025924797,
author = { Shailendra Singh Kathait, Ashish Kumar, Samay Sawal, Ram Patidar, Khushi Agrawal },
title = { Deep Learning-based Person Tracking: A Smart Approach to Security and Civic Monitoring },
journal = { International Journal of Computer Applications },
issue_date = { May 2025 },
volume = { 187 },
number = { 4 },
month = { May },
year = { 2025 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number4/deep-learning-based-person-tracking-a-smart-approach-to-security-and-civic-monitoring/ },
doi = { 10.5120/ijca2025924797 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-05-17T02:45:52.915404+05:30
%A Shailendra Singh Kathait
%A Ashish Kumar
%A Samay Sawal
%A Ram Patidar
%A Khushi Agrawal
%T Deep Learning-based Person Tracking: A Smart Approach to Security and Civic Monitoring
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 4
%P 1-4
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Restricted-area violations, such as entering into vehicle zones, create serious security issues in a variety of monitoring applications. This research presents a deep learning-based framework for realtime detection and surveillance of individuals who violate designated restricted zones. The proposed system uses advanced object detection algorithms, specifically YOLOv8, for head detection and spatial reasoning to track individuals who enter restricted areas. The framework uses centroid-based tracking to accurately detect and count violations, ensuring that each individual is flagged once within a frame only once. The method improves detection accuracy further by modifying bounding boxes and using regionspecific polygonal filtering, allowing for more exact violation detection. Visual feedback is provided by overlaying boundary boxes and labels on the detected individuals, while cumulative violation counts are recorded. This method is highly effective, providing stable performance in changing conditions, and can be used for crowd management, security, and surveillance. The system’s architecture is flexible, with the ability to add capabilities like movement direction and speed analysis for more context-aware violations.

References
  1. Ahmad, Misbah & Ahmed, Imran & Khan, Fakhri & Qayum, Fawad & Aljuaid, Hanan. (2020). Convolutional neural network–based person tracking using overhead views. International Journal of Distributed Sensor Networks. 16. 155014772093473. 10.1177/1550147720934738.
  2. Yu, S., Yang, Y., Li, X., & Hauptmann, A. G. (2016). Long-Term Identity-Aware Multi-Person Tracking for Surveillance Video Summarization. ArXiv. https://arxiv.org/abs/1604.07468
  3. Wang, Q., Zhang, L., Bertinetto, L., Hu, W., & Torr, P. H. (2018). Fast Online Object Tracking and Segmentation: A Unifying Approach. ArXiv. https://arxiv.org/abs/1812.05050
  4. Liem, Martijn & Gavrila, Dariu. (2013). A Comparative Study on Multi-person Tracking Using Overlapping Cameras. 203-212. 10.1007/978-3-642-39402-7 21.
  5. Pang, Z., Li, Z., & Wang, N. (2021). SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking. ArXiv. https://arxiv.org/abs/2111.09621
  6. Shailendra Singh Kathait, Ashish Kumar, Ram Patidar, Khushi Agrawal, Samay Sawal (2024). Computer Vision and Deep Learning based Approach for Traffic Violations due to Over-speeding and Wrong Direction Detection. International Journal of Computer Applications, paper-id: 6e503f15-f6c9- 4ee2-9212-4db588484729, DOI: 10.5120/ijca2025924477.
  7. Shailendra Singh Kathait, Ashish Kumar, Ram Patidar, Khushi Agrawal, Samay Sawal (2024). Computer Vision and Deep Learning based Approach for Violations due to Illegal Parking Detection. International Journal of Computer Applications, DOI: 10.5120/ijca2025924506
  8. Rupesh Parthe, The Importance of Centroid in Image Processing. INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, DOI: 10.55041/IJSREM30775
  9. Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi, You Only Look Once: Unified, Real-Time Object Detection. DOI: https://doi.org/10.48550/arXiv.1506.02640
  10. Shailendra Singh Kathait, Ashish Kumar, Ram Patidar, Khushi Agrawal, Samay Sawal (2024). Deep Learning-based Approach for Detecting Traffic Violations Involving No Helmet Use and Wrong Cycle Lane Usage. International Journal of Computer Applications, DOI: 10.5120/ijca2025924714
  11. Shailendra Singh Kathait, Shubhrita Tiwari, Application of Image Processing and Convolution Networks in Intelligent Character Recognition for Digitized Forms Processing, DOI: 10.5120/ijca2018915460.
Index Terms

Computer Science
Information Sciences

Keywords

Computer Vision Traffic Surveillance YOLO Vehicle Speed Detection Direction Detection Helmet Detection Lane Violation Non-ANPR Cameras