DocumentCode
2503174
Title
Super-Resolution Texture Mapping from Multiple View Images
Author
Iiyama, Masaaki ; Kakusho, Koh ; Minoh, Michihiko
Author_Institution
Kyoto Univ., Kyoto, Japan
fYear
2010
fDate
23-26 Aug. 2010
Firstpage
1820
Lastpage
1823
Abstract
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.
Keywords
image resolution; image texture; learning (artificial intelligence); mesh generation; realistic images; solid modelling; 3D mesh model; artifact-free super resolution texture mapping; cost function; image-and mesh assignment; learning-based super resolution technique; multiple view images; neighboring meshes; real images; super-resolution texture mapping; upscaled images; Computational modeling; Cost function; Image resolution; Minimization; Signal resolution; Solid modeling; Three dimensional displays; graph cut; super resolution; texture mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location
Istanbul
ISSN
1051-4651
Print_ISBN
978-1-4244-7542-1
Type
conf
DOI
10.1109/ICPR.2010.449
Filename
5597208
Link To Document