Papers by Author: Yan Feng Sun

Abstract: 3D face sample is an important data platform for model training, algorithm design. Subject to the constraint of data acquisition equipment the size of current 3D face databases are relatively small and insufficient. To solve this problem, this paper presents a modeling way for generating 3D novel samples based on surface stitching. First we use morphable model to build a global model. Then, we replace each patch of the global model based on surface stitching. We demonstrate that with appropriate choice of local models it is possible to reliably generate new realistic face samples.

Abstract: The traditional craniofacial reconstruction methods construct the face shape according to the soft tissue thickness measured at a sparse set of landmarks on the skull. But the landmarks are difficult to detect and generally need human interactive assistance. The quantity and position of the landmarks lack for uniform definition. We propose an automatic craniofacial reconstruction method based on a dense deformable model. To construct the model, hundreds of skull and face samples are acquired by CT scanner. A dense mesh registration algorithm is proposed to build the point-to-point correspondences of the samples. Based on the aligned samples, the deformable model is constructed. For a given skull, the reconstructed face is obtained by a model matching procedure. Experimental results indicate that the deformable model has good performance for craniofacial reconstruction.