Reconstructing Shape and Motion from Asynchronous Cameras

We present an algorithm for scene flow reconstruction from multi-view data. The main contribution is its ability to cope with asynchronously captured videos. Our holistic approach simultaneously estimates depth, orientation and 3D motion, as a result we obtain a quasi-dense surface patch representation of the dynamic scene. The reconstruction starts with the generation of a sparse set of patches from the input views which are then iteratively expanded along the object surfaces. We show that the approach performs well for scenes ranging from single objects to cluttered real world scenarios.