Action recognition is a hot research topic,but the performance assessment strategies of algorithms have not had an accepted practice.In this paper,we adopt spatio-temporal features and support vector machine(SVM) model as our action recognition algorithm,and then well assess the effect of different assessment strategies on our action recognition algorithm in widely used public dataset KTH.Experimental results show that when different cross-experimental methods are employed,the performance fluctuation of algorithms reaches 10.5%.And when different division methods for KTH datasets are used,the performance fluctuation of algorithms gets 11.87%.Thus,according to conclusions in this paper,we can find the real difference among existing algorithms,and supply the reference for designing reasonable assessment strategy.