Abstract: An articulated pose estimation method with part occlusion level is proposed for dealing with the lack of part information due to occlusion in monocular static images.Firstly,the occlusion level is defined as the occluded degree of human body parts,which is acquired by calculating the ratio of occlusion and orientation of parts; then,a more robust human body part model with occlusion level is established in order to decrease the interference caused by occlusion,and the deformable part model combined with occlusion level is introduced to indicate the relation between neighboring parts; finally,the proper human pose is estimated according to both the part model and deformable model.The experimental results on IP and LSP datasets show that our method improves the overall accuracy of the pose estimation,especially in the case of occlusion.