Video-and Location-based Analysis of Cycling Routes for Safety Measures and Fan Engagement

Abstract

Video-based analysis of cycling races can provide a lot of information that can be used to keep cycling interesting for the fans and improve cyclists' safety. In this paper, we propose a solution to collect and process the metadata of cycling races. The idea is to use edge computing, by collecting data from a car in front of the race and processing this data using a tailor-made setup. Our solution consists of a camera to record video, and a GPS module to map the corresponding locations. Both data streams are offered to a single board computer. The video frames are used for crowd size classification to roughly estimate the number of spectators present along the race route. Moreover, we use the same footage to recognize cyclists' names on the road's surface to determine the location of fans of specific cyclists to create metadata around fan engagement. The tailor-made system performs the processing of the video frames and the results are sent to a web server using a cellular network connection. A web application was created to visualize the crowd size and the location of cyclists' names on the road's surface.