Computer Vision, IEEE International Conference on (2005)
Oct. 17, 2005 to Oct. 20, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICCV.2005.218
Seyoun Park , Korea Advanced Institute of Science and Technology
Xiaohu Guo , State University of New York at Stony Brook
Hayong Shin , Korea Advanced Institute of Science and Technology
Hong Qin , State University of New York at Stony Brook
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.
H. Qin, S. Park, X. Guo and H. Shin, "Shape and Appearance Repair for Incomplete Point Surfaces," Computer Vision, IEEE International Conference on(ICCV), Beijing, China, 2005, pp. 1260-1267.