Real-Time Violence Detection and Alert System

Abstract

This paper presents a comprehensive implementation of a real-time violence detection and alert system that utilizes advanced machine learning (ML) and computer vision (CV) techniques to detect violent behaviours in video feeds. The system integrates an optimized combination of motion analysis, action recognition, and pose estimation accurately to identify the violent activities, such as fights or physical altercations, even in crowded or complex environments. Motion analysis serves as the initial step, highlighting areas with significant movement and reducing the computational burden by focusing on regions of interest. The recognition techniques, powered by deep learning models like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), then classify the detected movements as violent or non-violent. Pose estimation techniques further enhance the system’s ability to detect less visible violent gestures, such as hitting or aggressive body posture, by analyzing the movements of key body joints, even in partially obstructed views. Once a violent activity is identified, the system triggers an automated alert system that sends instant notifications to relevant authorities, including law enforcement and emergency services, providing essential details like location, timestamp, and severity. This ensures that authorities can intervene quickly, minimizing potential harm. The system’s scalability has been proven through extensive testing on real-world datasets and live CCTV feeds, demonstrating its ability to function efficiently across large areas with multiple cameras. Additionally, the system addresses key challenges such as operating in densely crowded spaces, ensuring computational efficiency for real-time processing, and maintaining high accuracy despite environmental complexities. Overall, the proposed solution offers a robust, scalable, and practical tool for enhancing public safety, capable of being integrated into existing surveillance infrastructures to detect and respond to violent incidents promptly.