How do children move and behave on streets? Vision-based movement behavior analysis using children's trajectories in urban surveillance systems

Abstract

Understanding how children use streets will allow urban planners to create streets that are livelier and more child-friendly. However, it is still challenging to investigate detailed information on children's movement behaviors on individual streets due to labor-intensive observations, the difficulty of integrating qualitative data, and privacy concerns. With the wide application of vision-based technologies, Researchers can analyze the movements and behaviors of large groups of children on streets automatically and continuously. This study aims to analyze children's movement behaviors on streets utilizing computer vision techniques in urban surveillance systems. The proposed methods automatically extract children's trajectories, calculate movement behavioral features, and classify the movement behavioral characteristics of children. Our results identify five movement behaviors of children on streets: walking, staying, running, accelerating, and decelerating, demonstrating their use of streets. In addition, the results showed the feasibility of computer vision techniques to identify differences in children's movement behaviors under varying conditions, such as day and time, and the potential of street environments to positively influence children's use of streets from the daily street lives of children. Utilizing vision-based analysis of children's movement behaviors provides meaningful information for improving streets for children toward a better understanding of the use of streets.