To deal with the modeling limitation in traditional morphable models

we present a compressed sensing based method for 3D face reconstruction. In the proposed framework

compressed sensing is first used to estimate the similarity between testing and prototype face samples

and a modified morphable model is then built on the selected prototype samples with larger similarity. Second

the model is registered to a test face image by using facial salient points. Finally

combining the shape recovered by the modified model and the shape obtained by RBFs interpolation

the testing shape is reconstructed. Experiments on the BJTU-3D face database and CAS-PEAL 2D face database show that the proposed method outperforms the traditional methods in both reconstruction accuracy and computation complexity. Moreover

its recovered 3D faces achieve higher realistic impressions. This paper presents a novel fast 3D face reconstruction method. The proposed modeling plan

based on selected prototype samples using compressed sensing

can effectively improve modeling precision and efficiency. Combined with the RBF smooth scheme

the proposed method can reconstruct face shape with high smoothness.