کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
528710 | 869603 | 2016 | 16 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Optimal depth recovery using image guided TGV with depth confidence for high-quality view synthesis Optimal depth recovery using image guided TGV with depth confidence for high-quality view synthesis](/preview/png/528710.png)
• A confidence-based depth recovery and high quality 3D view synthesis are proposed.
• The depth recovery relies on image edges and high depth confidence pixels.
• Texture directions of background are effective in hole filling for view synthesis.
This paper presents a new depth image recovery method for RGB-D sensors giving a complete, sharp, and accurate object shape from a noisy boundary depth map. The proposed method uses the image guided Total Generalized Variation (TGV) with the depth confidence. A new directional hole filling method of view synthesis is also investigated to produce natural texture in hole regions whereas reducing blurring effect and preventing distortion. Thus, a high-quality image view can be achieved. Experimental results show that the proposed method yields higher quality recovered depth maps and synthesized image views than other previous methods.
Journal: Journal of Visual Communication and Image Representation - Volume 39, August 2016, Pages 24–39