A Fast Multi-object Tracking Algorithm by Fusing Color and Motion Information

This paper proposes a fast algorithm for multiple targets tracking in complex environment of industrial workshop, which integrates the background modeling and the motion information. First, the probability density image is calculated based on histogram of color from each target object. Second, these probability density images are filtered according to background image obtained from previous background modeling. Third, the motion information is fused into its tracking process, and the optimal position is thus predicted. Finally, the algorithm removes the false targets in the previous frame from those images of color probability density, in order to avoid the disturbance to other targets in the later tracking procedure. The experimental results have demonstrated that the proposed new algorithm is capable of reducing background and similar objects disturbance and achieving real-time performance.