Shape preserving RGB-D depth map restoration

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Abstract

The RGB-D cameras have enjoined a great popularity these years. However, the quality of the depth maps obtained by such cameras is far from perfect. In this paper, we propose a framework for shape preserving depth map restoration for RGB-D cameras. The quality of the depth map is improved from three aspects: 1) the proposed region adaptive bilateral filter (RA-BF) smooths the depth noise across the depth map adaptively, 2) by associating the color information with the depth information, incorrect depth values are adjusted properly, 3) a selective joint bilateral filter (SJBF) is proposed to successfully fill in the holes caused by low quality depth sensing. Encouraging performance is obtained through our experiments.

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Liu, W., Xue, H., Gu, Y., Yang, J., Wu, Q., & Jia, Z. (2014). Shape preserving RGB-D depth map restoration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8836, pp. 150–158). Springer Verlag. https://doi.org/10.1007/978-3-319-12643-2_19

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