Abstract

In this paper, we address the problem of surface tracking in multiple camera environments and over time sequences. In order to fully track a surface undergoing signi ficant deformations, we cast the problem as a mesh evolution over time. Such an evolution is driven by 3D displacement fields estimated be- tween meshes recovered independently at different time frames. Geometric and photometric information is used to identify a robust set of matching vertices. This provides a sparse displacement field that is densi fied over the mesh by Laplacian diffusion. In contrast to existing approaches that evolve meshes, we do not assume a known model or a fixed topology. The contribution is a novel mesh evolution based framework that allows to fully track, over long sequences, an unknown sur- face encountering deformations, including topological changes. Results on very challenging and publicly available image based 3D mesh sequences demonstrate the ability of our framework to efficiently recover surface motions .