Rapid Skin: Estimating the 3D Human Pose and Shape in Real-Time

We present a novel approach to adapt a watertight polygonal model of the human body to multiple synchronized camera views. While previous approaches yield excellent quality for this task, they require processing times of several seconds, especially for high resolution meshes. Our approach delivers high quality results at interactive rates when a roughly initialized pose and a generic articulated body model are available. The key novelty of our approach is to use a Gauss-Seidel type solver to iteratively solve nonlinear constraints that deform the surface of the model according to silhouette images. We evaluate both the visual quality and accuracy of the adapted body shape on multiple test persons. While maintaining a similar reconstruction quality as previous approaches, our algorithm reduces processing times by a factor of 20. Thus it is possible to use a simple human model for representing the body shape of moving people in interactive applications.