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Article Dans Une Revue IEEE Transactions on Image Processing Année : 2017

Depth-guided disocclusion inpainting of synthesized RGB-D images

Résumé

We propose to tackle the disocclusion inpainting of RGB-D images when synthesizing new views of a scene by changing its viewpoint. Such a process creates holes both in depth and color images. First, we propose a novel algorithm to perform the depth-map disocclusion inpainting. In particular, this intuitive approach is able to recover the lost structures of the objects and to inpaint the depth-map in a geometrically plausible manner. Then, we propose a depth-guided patch based inpainting method to fill-in the color image. Depth information coming from the reconstructed depth-map is added to each key step of the classical patch-based algorithm from Criminisi et al. in an intuitive manner. Relevant comparisons to state-of-the-art inpainting methods for the disocclusion inpainting of both depth and color images are provided and illustrate the effectiveness of our proposed algorithms.
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Dates et versions

hal-01391065 , version 1 (02-11-2016)

Identifiants

Citer

Pierre Buyssens, Olivier Le Meur, Maxime Daisy, David Tschumperlé, Olivier Lézoray. Depth-guided disocclusion inpainting of synthesized RGB-D images. IEEE Transactions on Image Processing, 2017, 26 (2), pp.525-538. ⟨10.1109/TIP.2016.2619263⟩. ⟨hal-01391065⟩
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