Reparation of transparency for high-quality three-dimensional reconstruction using a single RGB-D sensor

Abstract

Consumer-grade range cameras are widely used in three-dimensional reconstruction. However, the resolution and stability limit the quality of reconstruction, especially with transparent objects. A method is proposed to reconstruct the transparency while improving the reconstruction quality of the indoor scene with a single RGB-D sensor. We propose the method to localize the transparent regions from zero depth and wrong depth. The lost surface of transparency is recovered by modeling the statistics of zero depth, variance, and residual error of signed distance function (SDF) with depth data fusion. The camera pose is first initialized by the error minimization of depth map on the SDF and k-color-frame constraint. The pose then is optimized by the penalized coefficient function, which lowers the weight of voxels with higher SDF error. The method is proved to be valid in localizing the transparent objects and can achieve a more robust camera pose under a complex background.