In order to carry on the gait recognition fast and effectively，aiming at the characteristics that gait energy image can view the information of gait and two dimension principal component analysis can reduce the dimensions quickly，a novel gait recognition based on gait energy image and two dimension principal component analysis is proposed in this paper.Firstly，the body silhouette extraction is achieved by background subtraction.Secondly，a gait cycle is obtained with the correlated signal of the ratio of width and height of human body.Gait energy image is applied on the binary image sequence to construct the feature vector.Finally，(2D)2PCA and W(2D)2PCA is used to reduce into a low dimension space.The nearest-neighbor classifier is adopted to distinguish the difference.This gait recognition method can decrease the influence of the early preprocess effectively，and our experimental results demonstrate that the method is effective and has achieved a good recognition effect on CASIA gait database including three different multi-views.