  Multi-object tracking (MOT) or global data association problem is commonly
approached as a minimum-cost-flow or minimum-cost-circulation problem on a
graph. While there have been numerous studies aimed at enhancing algorithm
efficiency, most of them focus on the batch problem, where all the data must be
available simultaneously to construct a static graph. However, with the growing
number of applications that generate streaming data, an efficient online
algorithm is required to handle the streaming nature of the input. In this
paper, we present an online extension of the well-known negative cycle
canceling algorithm for solving the multi-object tracking problem with
streaming fragmented data. We provide a proof of correctness for the proposed
algorithm and demonstrate its efficiency through numerical experiments.
