In order to improve the efficiency of tracking algorithm based on distribution fields and the robustness of the algorithm under complex background,tracking algorithm by compressive distribution fields with adaptive hierarchical structure is presented.Distribution of pixel values in target region is considered in this method,k-means algorithm is introduced to analyse the distribution of pixel values in the first frame,adaptive hierarchical structure of distribution fields is built according to the clustering results.For the problem that the dimension of distribution field model is high,compressive sensing is combined to compress distribution fields,which can reduce the model dimension and improve the efficiency of tracking algorithm.Furthermore,local search strategy in original distribution fields tracking algorithm is changed,random sampling is used to improve the tracking accuracy.Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art tracking algorithms.
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2017, Vol. 45 
