counting people passing door

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counting people passing door

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Counting People Passing Through a Door

Counting people passing through a door is a common problem in various domains, including retail analytics, security surveillance, and space occupancy monitoring. The task involves detecting and tracking individuals as they enter or exit a designated area.

One approach to solving this problem involves using computer vision techniques. Here’s a high-level breakdown of the process:

Motion Detection – The system first identifies movement near the door using background subtraction or frame differencing to isolate moving objects. Object Detection – A trained model (such as YOLO or SSD) identifies human figures within the frame, distinguishing them from other moving objects like carts or pets. Tracking & Direction Analysis – Algorithms like Kalman filters or centroid tracking help follow the movement of individuals, determining whether they are entering or exiting based on their trajectory. Counting Logic – By analyzing crossing events (when a person passes a virtual line near the door), the system increments or decrements the count accordingly.

Challenges include occlusion (people walking in groups), varying lighting conditions, and distinguishing between entries and exits. Advanced solutions may integrate deep learning for better accuracy in crowded scenarios.

This technology has applications in foot traffic analysis, smart building automation, and security systems, making it a valuable tool for data-driven decision-making.