To overcome the problem that traditional Iterative Closest Point (ICP) can’t properly handle the situation of outliers, noise and missing data appeared in the process of image processing which would result in low accuracy of image registration. An enhanced Sparse Iterative Closest Point (SICP) to register the 3D point cloud is proposed, and sparse ICP address these problems by formulating the registration optimization using sparsity inducing norms. What’s more, a fast head segmentation algorithm was proposed to segment the user’s head in depth image. Based on the proposed fast face segmentation algorithm and sparse ICP, a new 3D face modeling system is put forward. The experimental results demonstrate the effectiveness of the proposed algorithm