Dense and Accurate Spatio-temporal Multi-view Stereovision

In this paper, we propose a novel method to simultaneously and accurately estimate the 3D shape and 3D motion of a dynamic scene from multiple-viewpoint calibrated videos. We follow a variational approach in the vein of previous work on stereo reconstruction and scene flow estimation. We adopt a representation of a dynamic scene by an animated mesh, i.e. a polygonal mesh with fixed connectivity whose timevarying vertex positions sample the trajectories of material points. Interestingly, this representation ensures a consistent coding of shape and motion by construction. Our method accurately recovers 3D shape and 3D motion by optimizing the positions of the vertices of the animated mesh. This optimization is driven by an energy function which incorporates multi-view and inter-frame photo-consistency, smoothness of the spatio-temporal surface and of the velocity field. Central to our work is an image-based photo-consistency score which can be efficiently computed and which fully hand...

• Type: Conference
• Year: 2009
• Where: ACCV
• Authors: Jérôme Courchay, Jean-Philippe Pons, Pascal Monasse, Renaud Keriven
• Keywords: ACCV 2009, Computer Vision, Dynamic Scenes, Multiple-viewpoint Calibrated Videos, Scene flow Estimation