Fast and High Quality Fusion of Depth Maps
Christopher Zach · 2008
Reconstructing the 3D surface from a set of provided range images – acquired by active or passive sensors – is an important step to generate faithful virtual models of real objects or environments. Since several approaches for high quality fusion of range images are already known, the run-time efficiency of the respective methods are of increased interest. In this paper we propose a highly efficient method for range image fusion resulting in very accurate 3D mod-els. We employ a variational formulation for the surface reconstruction task. The global optimal solution can be found by gradient descent due to the convexity of the under-lying energy functional. Further, the gradient descent pro-cedure can be parallelized, and consequently accelerated by graphics processing units. The quality and runtime per-formance of the proposed method is demonstrated on well-known multi-view stereo benchmark datasets. 1.