We address the problem of super resolved generation of novel views of a 3D scene with the reference images obtained from cameras in general positions; a problem which has not been tackled before in the context of super resolution and is also of importance to the field of image based rendering. We formulate the problem as one of estimation of the color at each pixel in the high resolution novel view without explicit and accurate depth recovery.We employ a reconstruction based approach using MRF-MAP formalism and solve using graph cut optimization. We also give an effective method to handle occlusion. We present compelling results on real images.
Super Resolution of Images of 3D Scenecs
Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007
01.01.2007
11 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
View Synthesis , Candidate Depth , Input Image , Super Resolution , Dominant Cluster Pattern Recognition , Artificial Intelligence , Algorithm Analysis and Problem Complexity , Computer Science , Biometrics , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics
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