Publication
Camera-based position analysis system for cyclists ordering in bicycle swarms
Vemburaj Yadav; Alain Pagani; Didier Stricker
In: Workshop on Smart Urban Micromobility. Mensch und Computer (MuC-2023), September 3-6, Zürich, Switzerland, ACM, 2023.
Abstract
Cycling in swarms has gained popularity as a social and fitness
activity. To offer enhanced digital services for swarm cycling, it
is essential to obtain real-time information about the position of
each cyclist within the swarm. While GNSS (Global Navigation
Satellite Systems) signals such as GPS, Galileo or GLONASS may not
provide precise positioning in such scenarios, this paper proposes a
novel approach to address this challenge. By equipping each bicycle
with a backward-facing camera and leveraging computer vision
and deep learning methodologies, we can achieve the absolute
ordering of bicyclists in real-time. This position paper outlines a
comprehensive framework that utilizes object detection, monocular
depth estimation, and object tracking models to process camera
information and obtain accurate positioning within the swarm. The
proposed solution also enables the detection of overtakes between
cyclists, adding an additional layer of information to enhance the
overall swarm cycling experience.