Reconstruction of 3D dynamic expressions from single facial image

Recently automatic facial expression analysis and recognition is rapidly gaining more and more interest in the field of computer vision. The capture and construction of 3D dynamic expressions often take large time and need specialized hardware, which limits its possible applications. In this paper, we try to reconstruct 3D dynamic expression images from single 2D facial image. The proposed method is based on statistical learning, where multiple subspaces are learned and support for 3D dynamic expression generation. The results show that the proposed method can effectively generate 3D dynamic expressions using only one input 2D facial image.