The weight of the truth,indeterminacy,and falsity membership under the neutrosophic framework may be different when dealing with different problems.Due to this,a component weighted cosine similarity coefficient was proposed,and it was introduced into the mean shift tracking algorithm.Firstly,the corresponding methods for calculating the membership of the truth,indeterminacy,and falsity were proposed based on the theory of 3σ,as well as the similarity between the features of the corresponding area of the object and background.Then the weighted cosine similarity coefficient was used to construct the weight vector.In addition,a weighted cosine similarity coefficient based scale updating method was proposed.The experimental results demonstrate that the modified visual tracking algorithm performs well,even when there exists challenges like similar background,illumination or scale variation.