  Due to better video quality and higher frame rate, the performance of
multiple object tracking issues has been greatly improved in recent years.
However, in real application scenarios, camera motion and noisy per frame
detection results degrade the performance of trackers significantly. High-speed
and high-quality multiple object trackers are still in urgent demand. In this
paper, we propose a new multiple object tracker following the popular
tracking-by-detection scheme. We tackle the camera motion problem with an
optical flow network and utilize an auxiliary tracker to deal with the missing
detection problem. Besides, we use both the appearance and motion information
to improve the matching quality. The experimental results on the VisDrone-MOT
dataset show that our approach can improve the performance of multiple object
tracking significantly while achieving a high efficiency.
