A new approach is proposed in real-time specified object tracking system under auto dome rotation freely. When it is necessary to track objects in occlusion conditions or with high speed by real-time system, it is not always possible to using particle filter or mean shift algorithm both of which are widely used. The key idea of the presented research work is to integrate the advantages of mean-shift algorithm and particle filter. Using mean shift algorithm to iterate the particles generated by particle filter repeatedly until stable, which could efficiently reduces the number of sampled particles. Therefore the system designed in this paper can track the objects in occlusion conditions or with high speed, and the computational cost is greatly reduced, moreover, an adaptive occlusion detecting algorithm, which update the model when the object is in occlusion makes the system more robust. The experiment results demonstrate that the object tracking system in this paper can meet the tracking requirements when the object is moving, rotating or in partial occlusion. The error of this system is less than 0.859%, it also proved the combing method is effective and steady.
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