A motion model is used to overcome the shortcoming of the low tracking accuracy of a kernelized correlation filter (KCF) based only on a target appearance model. The intersection-over-union (IOU) between the detection target bounding box and the predicted target bounding box was calculated. The optimal correlation among the targets was determined using the Hungarian algorithm. Both the KCF and IOU models are characterized by fast responses; therefore, the algorithm has the ability to process data online. The experiments were conducted on the public 2DMOT2015 and MOT16 datasets. Compared with the other state-of-the-art method, the tracking accuracy of the proposed method is higher than 10% while ensuring a processing speed of 30 frame/s or faster.