Super-Resolution Texture Mapping from Multiple View Images

This paper presents an artifact-free super resolution texture mapping from multiple-view images. The multiple-view images are upscaled with a learning-based super resolution technique and are mapped onto a 3D mesh model. However, mapping multiple-view images onto a 3D model is not an easy task, beca...

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Bibliographic Details
Main Authors: Iiyama, M, Kakusho, K, Minoh, M
Format: Conference Proceeding
Language:English
Subjects:
Computational modeling
Cost function
graph cut
Image resolution
Minimization
Signal resolution
Solid modeling
super resolution
texture mapping
Three dimensional displays
Online Access:Request full text
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Description
Summary:This paper presents an artifact-free super resolution texture mapping from multiple-view images. The multiple-view images are upscaled with a learning-based super resolution technique and are mapped onto a 3D mesh model. However, mapping multiple-view images onto a 3D model is not an easy task, because artifacts may appear when different upscaled images are mapped onto neighboring meshes. We define a cost function that becomes large when artifacts appear on neighboring meshes, and our method seeks the image-and mesh assignment that minimizes the cost function. Experimental results with real images demonstrate the effectiveness of our method.
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2010.449