Abstract
As technology advances, improving the accuracy of image target tracking is extremely important for medicine, aerospace and military, industry and agriculture. Image target tracking usually apply the method of manual extraction, which is not only a waste of time and power, but also has many difficulties in extraction. However, multi target algorithm can make up for its shortcomings, and multi target algorithm develops from underlying characteristics to multi-level, abstract features in the form of data. This paper, proposed a novel multi target algorithm for image target tracking for solving the above shortcomings. In the multi-target tracking problem, the random set is actually the number of elements and a set of random variables. When the number of targets is unknown or changing, the number of targets is a discrete random variable, the dimension of the state space will be different with the target value of the number of changes, so the multi target state model and observation model can be expressed as random finite sets form. Simulation results show that compared with traditional method, this method has higher accuracy and low loss rate.
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