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Edge-aware depth completion for point-cloud 3D scene visualization on an RGB-D camera

Nowadays, 3D scene reconstruction using RGB-D videos becomes more popular because of the widely-available off-the-shelf RGB-D camera. However, the depth information from current RGB-D camera still need improved in order to reconstruct the 3D scene with better quality. In this paper, an edge-aware depth completion method aims to recover more accurate depth information is proposed. There are mainly two parts in our proposed method. The first part is the edge-aware color image analysis, and the second part is depth image processing including unreliable depth pixel invalidation and filling. The depth image processing can retrieve more accurate depth information using our proposed edge-aware color image analysis. Consequently, we can not only preserve the reliable depth information, but also fill in the appropriate depth values to align edges of depth image with edges of its corresponding color image. Besides, the experimental results show that the visualization of the reconstructed point-cloud 3D scene benefits from our proposed edge-aware depth completion. Finally, the PSNR evaluation using ground truth depth information is presented.