Title :
Unwrapping low-rank textures on generalized cylindrical surfaces
Author :
Zhang, Zhengdong ; Liang, Xiao ; Ma, Yi
Abstract :
In this paper, we show how to reconstruct both 3D shape and 2D texture of a class of surfaces from a single perspective image. We consider the so-called the generalized cylindrical surfaces that are wrapped with low-rank textures. They can be used to model most curved building facades in urban areas or deformed book pages scanned for text recognition. Our method leverages on the recent new techniques for low-rank matrix recovery and sparse error correction and it generalizes existing techniques from planar surfaces to a much larger class of important 3D surfaces. As we will show with extensive simulations and experiments, the proposed algorithm can precisely rectify deformation of textures caused by both perspective projection and surface shape. It works for a wide range of symmetric or regular textures that are ubiquitous in images of urban environments, objects, or texts, and it is very robust to sparse occlusion, noise, and saturation.
Keywords :
computational geometry; computer vision; error correction; image reconstruction; image texture; matrix algebra; shape recognition; text analysis; 2D texture reconstruction; 3D shape reconstruction; computer vision; curved building facades; deformed book pages; generalized cylindrical surfaces; low-rank matrix recovery; low-rank texture unwrapping; sparse error correction; text recognition; texture deformation rectification; Cameras; Jacobian matrices; Mathematical model; Shape; Surface reconstruction; Surface texture; Three dimensional displays;
Conference_Titel :
Computer Vision (ICCV), 2011 IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4577-1101-5
DOI :
10.1109/ICCV.2011.6126388