Improved Reconstruction of Deforming Surfaces by Cancelling Ambient Occlusion

Abstract

We present a general technique for improving space-time reconstructions of deforming surfaces, which are captured in an video-based reconstruction scenario under uniform illumination. Our approach simultaneously improves both the acquired shape as well as the tracked motion of the deforming surface. The method is based on factoring out surface shading, computed by a fast approximation to global illumination called ambient occlusion. This allows us to improve the performance of optical flow tracking that mainly relies on constancy of image features, such as intensity. While cancelling the local shading, we also optimize the surface shape to minimize the residual between the ambient occlusion of the 3D geometry and that of the image, yielding more accurate surface details in the reconstruction. Our enhancement is independent of the actual space-time reconstruction algorithm. We experimentally measure the quantitative improvements produced by our algorithm using a synthetic example of deforming skin, where ground truth shape and motion is available. We further demonstrate our enhancement on a real-world sequence of human face reconstruction.