DocumentCode
2590149
Title
Shape and appearance repair for incomplete point surfaces
Author
Park, Seyoun ; Guo, Xiaohu ; Shin, Hayong ; Qin, Hong
Author_Institution
KAIST, Daejeon
Volume
2
fYear
2005
fDate
17-21 Oct. 2005
Firstpage
1260
Abstract
This paper presents a new surface content completion framework that can restore both shape and appearance from scanned, incomplete point set inputs. First, the geometric holes can be robustly identified from noisy and defective data sets without the need of any normal or orientation information, using the method of active deformable models. The geometry and texture information of the holes can then be determined either automatically from the models´ context, or semi-automatically with minimal users´ intervention. The central idea for this repair process is to establish a quantitative similarity measurement among local surface patches based on their local parameterizations and curvature computation. The geometry and texture information of each hole can be completed by warping the candidate region and gluing it to the hole. The displacement for the alignment process is computed by solving a Poisson equation in 2D. Our experiments show that the unified framework, founded upon the techniques of deformable models, local parameterization, and PDE modeling, can provide a robust and elegant solution for content completion of defective, complex point surfaces
Keywords
Poisson equation; computational geometry; image denoising; image restoration; image texture; PDE modeling; Poisson equation; active deformable model; alignment process; appearance repair; curvature computation; geometric hole; geometry information; incomplete point surface; local parameterization; local surface patch; minimal user intervention; model context; quantitative similarity measurement; shape repair; surface content completion; texture information; Active noise reduction; Clouds; Computer vision; Context modeling; Deformable models; Information geometry; Noise shaping; Robustness; Shape; Solid modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
Conference_Location
Beijing
ISSN
1550-5499
Print_ISBN
0-7695-2334-X
Type
conf
DOI
10.1109/ICCV.2005.218
Filename
1544865
Link To Document