A study of some super resolution techniques in video sequence

Riedinger, Christophe; Khemakhem, Mohamed; Chollet, G.

doi:10.1109/setit.2012.6481946

Cited by 1 publication

(1 citation statement)

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“…Super-resolution Facial texture modeling from images of poor resolution shares similarities with super-resolution problems [7,19,22,25]. However, unlike classical 2D super-resolution, multiple images of a face are unlikely to differ only by sub-pixel translations and rotations in the image plane.…”

Section: Related Workmentioning

confidence: 99%

Example-Based Modeling of Facial Texture from Deficient Data

Dessein

Smith

Wilson

et al. 2015

2015 IEEE International Conference on Computer Vision (ICCV)

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We present an approach to modeling ear-to-ear, highquality texture from one or more partial views of a face with possibly poor resolution and noise. Our approach is example-based in that we reconstruct texture with patches from a database composed of previously seen faces. A 3D morphable model is used to establish shape correspondence between the observed data across views and training faces. The database is built on the mesh surface by segmenting it into uniform overlapping patches. Texture patches are selected by belief propagation so as to be consistent with neighbors and with observations in an appropriate image formation model. We also develop a variant that is insensitive to light and camera parameters, and incorporate soft symmetry constraints. We obtain textures of higher quality for degraded views as small as 10 pixels wide, than a standard model fitted to non-degraded data. We further show applications to super-resolution where we substantially improve quality compared to a state-of-the-art algorithm, and to texture completion where we fill in missing regions and remove facial clutter in a photorealistic manner.

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Section: Related Workmentioning

confidence: 99%