Real-Time People Tracking and Counting

Project Description:

This project leverages YOLO11 for real-time object detection and tracking in video footage. It is specifically designed to track people in a site video and assign unique tracking IDs to detected objects. The tracking process persists across frames, enabling accurate monitoring.

The YOLO11 model is used to detect objects, and bounding boxes with unique track IDs are drawn on the video. The object class names are retrieved from the model, allowing the system to identify detected objects accurately. The tracking results are displayed using OpenCV and CvZone, enhancing visualization with structured text overlays.

This system can be adapted for various applications, including site monitoring, tracking, and safety.

Key Features:

• Uses YOLO11 for object detection and tracking.
• Extracts bounding boxes, class IDs, track IDs, and confidence scores.
• Displays results in real time using OpenCV and CvZone.
• Implements frame skipping for efficient processing.
• Supports video file input, but can be modified for webcam usage.

Potential Applications:

•  Site Monitoring: Track peoples, and workers.
• Equipment Tracking: Monitor movement and status.
• Security Surveillance: Identify and track objects in restricted areas.
• Traffic and Vehicle Analysis: Adaptable for tracking in surveillance.

Use Cases:

1.  Site Monitoring

   • Track people in real time.
   • Enhance safety compliance by monitoring restricted zones.

2.  Tracking

   • Monitor movements  within a site.
   • Reduce theft risk by tracking unauthorized movements.

3. Security and Surveillance

   • Detect unauthorized personnel in restricted areas.
   • Provide automated tracking for large-scale security systems.

4.  Analysis

   • Adapt for surveillance to track patterns.
   • Analyze movements for smart city planning.

Conclusion:

This project provides a scalable, adaptable, and efficient solution for people tracking in videos. By utilizing YOLO11 advanced detection capabilities, it enables precise tracking for applications in security, asset management, and monitoring. The framework can be further extended to support real-time decision-making, automation, and AI-driven analytics.