This report presents the development and implementation of a multi-camera multiperson
tracking system in an operating room, capable of tracking several people,
which aims to enable behavioral research of medical staff members during surgery,
in order to improve the understanding of interactions and work processes of doctors
and officials during surgical procedures. To this end, we designed and created
a software pipeline system that combines advanced technologies in the field of
computer vision and tracking, along with innovative algorithms, such as BoT-SORT
and Vision Transformers. The system is designed to accurately track multiple
people at the same time using different synchronous camera videos within the
dynamic and complex environment of an operating room. Through the use of
advanced algorithms and models, our solution enables correct identification and
re-identification of medical staff members, and manages to overcome challenges
unique to the operating room setting, such as the similar outfits of medical staff
and mask usage, which prevent the use of typical facial recognition