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January 1, 2025The International Arab Journal of Information TechnologyOpen Access

Deep Learning-Based Control System for Context-Aware Surveillance Using Skeleton Sequences from IP and Drone Camera video

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Authors

VSVasavi SanikommuSiddhartha Medical CollegeMSM. SobhanaSiddhartha Medical CollegeNJNovaline JacobGovernment of India

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Overview

Hybrid methodology integrates face and human activity recognition in surveillance settings, suggesting enhanced monitoring capabilities.

Key Points

  • The system achieved a classification accuracy of 0.99 for face recognition, significantly enhancing security measures.
  • An ensemble model effectively classifies six activities, including walking, standing, and punching, improving situational awareness.
  • The integration of skeleton sequences enhances the accuracy of human activity recognition, which is crucial for real-time applications.
  • This system can generate warnings for abnormal activities, potentially aiding law enforcement and security personnel.

Cite This Study

Sanikommu et al. (2025) studied this question.

synapsesocial.com/papers/68af5f13ad7bf08b1eae1f8ehttps://doi.org/10.34028/iajit/22/5/6
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