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One-To-One Person Re-Identification For Queue Time Estimation

Queue time measurements in airport check-points are essential in order to regulate staff allocation and maintain a low queue time. In this paper, we propose a method to measure queue times based on person re-identification. Specifically, we capture passenger features from entrance and exit points of an airport check-point and match features to determine queue times of passengers. However, a passenger seen at the exit, potentially, can be matched to multiple passengers seen at the entrance. Therefore, to increase the precision of re-identification, we propose a simple, yet effective, algorithm that assigns each passenger seen at the exit to only a single passenger seen at the entrance. Through experiments on a dataset collected from an airport immigration check-point, we show that our proposed assignment increases precision and recall by 22 % and 16 %, respectively, to naively assigning the best match.