  3D sensors, also known as RGB-D sensors, utilize depth images where each
pixel measures the distance from the camera to objects, using principles like
structured light or time-of-flight. Advances in artificial vision have led to
affordable 3D cameras capable of real-time object detection without object
movement, surpassing 2D cameras in information depth. These cameras can
identify objects of varying colors and reflectivities and are less affected by
lighting changes. The described prototype uses RGB-D sensors for bidirectional
people counting in venues, aiding security and surveillance in spaces like
stadiums or airports. It determines real-time occupancy and checks against
maximum capacity, crucial during emergencies. The system includes a RealSense
D415 depth camera and a mini-computer running object detection algorithms to
count people and a 2D camera for identity verification. The system supports
statistical analysis and uses C++, Python, and PHP with OpenCV for image
processing, demonstrating a comprehensive approach to monitoring venue
occupancy.
