A Real-time Queue Tracking Method for Waiting Time Estimation

Abstract

In daily life, people spend a significant part of their time waiting in queues at numerous places such as banks, airports, cafeterias and market cash registers. Various queue analysis and management tools have been developed to reduce this wasted time. One of these tools is the systems that analyze the queues and calculate the average waiting time. In this study, a computer vision method that calculates the average waiting time by detecting and tracking the people waiting in the queue is proposed. Thanks to this method, it is aimed that people can see how long they will wait before queuing. In the developed method, people waiting in a direction were analyzed by using object detection methods, and the times of joining and leaving the queue were tried to be determined. Due to the high processing load of the object detection algorithms, object tracking algorithms are used so that the method can work in real-time. The method developed according to the experimental studies can process the 640×480 resolution video on a mid-level GPU with %88.46 accuracy and speeds up to 95.51 fps.