Multiview Normal Field Integration using Graph-Cuts

While there are many algorithms which address the reconstruction of partial surfaces from single-view normal fields, to the best of our knowledge, there is only one method [Chang et al., ’Multiview Normal Field Integration using Level Sets’, CVPR 2007] which focuses on the reconstruction of the full shape of an object from multiple normal fields captured from multiple viewpoints. In this paper, we propose an alternative approach for the integration of such normal fields. We use a similar energy formulation as Chang et al., but replace the employed levelset representation with a graph-cut based reconstruction. Based on the visual hull of the object we estimate the visibility from each viewpoint. Then we project estimated normal fields to the visual hull and the optimal surface is computed by maximizing the flux of the obtained vector field through the surface. The graph-cut approach allows for a fast and globally consistent optimization of the given problem. Finally, we demonstrate the validity of our algorithm on synthetic data sets.