Development of a wide-area pedestrian trajectory measurement system using multiple camera images

Abstract

Data such as pedestrian traffic volume and pedestrian trajectories are used as basic data for urban redevelopment and revitalization planning. In this study, we developed a technology for determining pedestrian trajectories from mul- tiple cameras using Deep Learning and Gradient Boosting, which are artificial intelligence (AI) technologies. Specifi- cally, we improved the accuracy by determining the same person based on the location information of the person de- tected by the Deep Learning model, and then tracking the estimated trajectory using the Gradient Boosting model. As a result of demonstration experiments, the trajectory of a person can be determined even when the person moves across the camera, indicating that this technology may be effective in improving and saving labor for pedestrian traffic volume and pedestrian trajectory measurement.