Automated People Counting System

Within the realm of computer vision, accurate people counting through video analysis is crucial, especially for crowd management and security applications. This paper introduces a system focused on automatically determining the count of individuals in both indoor and outdoor settings using a single camera and implementing it through Python-based OpenCV. The system extracts frames from video streams, establishes reference lines, detects individuals using the MobileNet-SSD object detection model, marks centroids on detected persons, tracks their movements, and determines the direction of movement to categorize entries or exits. Such technology is crucial not only for ensuring transportation safety but also for various businesses, especially smaller ones lacking extensive data for decision-making. The intelligent utilization of people counting data can significantly impact business operations beyond basic visitor statistics, shaping decisions and strategies effectively.