Multi-camera multi-person tracking with DeepSORT and MySQL - Raghavendra, Shashank Horakodige; Sorapalli, Yashasvi; Poojar S. V., Nehashri; Maddirala, Hrithik; Kumar P., Ramakanth; Nasreen, Azra; Trivedi, Neeta; Agarwal, Ashish; K., Sreelakshmi (Indonesian Journal of Electrical Engineering and Computer Science, 2025)
Multi-camera multi-object tracking refers to the process of simultaneously tracking numerous objects using a network of connected cameras. Constructing an accurate depiction of an object’s movements requires the analysis of video data from many camera feeds, detection of items of interest, and their association across various camera perspectives. The objective is to accurately estimate the trajectories of the objects as they navigate through a monitored area. It has several uses, including surveillance, robotics, self-driving cars, and augmented reality. The current version of an object tracking algorithm, DeepSORT, doesn’t account for errors caused by occlusion or implementation of multiple cameras. In this paper, DeepSORT has been extended by introducing new states to improve the tracking performance in scenarios where objects are occluded in the presence of multiple cameras. The communication of track information across multiple cameras is achieved with the help of a database. The suggested system performs better in situations where objects are occluded, whether due to object occlusions or person occlusions.