Abstract:The application of sparse representation in target tracking system is discussed． Thesparse representation of target feature is achieved by solving an L1 regularized least squares problem，then the candidate with the smallest target template projection error is chosen as the tracking result．The templates are updated to adapt to the change of the object of tracking． Optimal tracking resultsare obtained through combining the Bayes framework based hypothesis with the templates of image sequences． Experiments show that the method is effective．