Example-based human motion extrapolation based on manifold learning

Abstract

In this paper, we propose a new framework to synthesize human motions based on only one single posture given in the input image. To generate visually pleasing motion sequences, the proposed framework consists of two key techniques. One is motion retrieval, which retrieves reference motions from a human motion database on a low-dimensional motion manifold. Another one is human motion extrapolation, which first generates new postures by deforming the shape of the input posture according to the retrieved motions and then synthesizes the corresponding motion sequence. To demonstrate the efficacy of the proposed method, we generate several human motion sequences using input images with different postures and show that the results are indeed visually pleasing.