Please use this identifier to cite or link to this item:
Title: Detecting discontinuities for surface reconstruction
Authors: Wang, Y.
Bu, J.
Li, N.
Song, M.
Tan, P. 
Issue Date: 2012
Citation: Wang, Y.,Bu, J.,Li, N.,Song, M.,Tan, P. (2012). Detecting discontinuities for surface reconstruction. Proceedings - International Conference on Pattern Recognition : 2108-2111. ScholarBank@NUS Repository.
Abstract: Photometric stereo algorithms produce a map of normal directions from the input images. The 3D surface can be reconstructed from this normal map. Existing surface reconstruction works often assume the normal map is integrable but contaminated by small scale non-integrable noise. However, real surfaces often contain large discontinuities such as occlusion boundaries and sharp depth changes, which break the integrable assumption commonly made in many works. Here, we propose a method to detect these discontinuities by combining multiple geometric cues with trained classifiers and a simple graph optimization. The surface is then reconstructed with the guidance of these detected discontinuities. Experiments show our method outperforms existing works. © 2012 ICPR Org Committee.
Source Title: Proceedings - International Conference on Pattern Recognition
ISBN: 9784990644109
ISSN: 10514651
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

checked on Jan 27, 2020

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.