A Robust Scheme for Feature-Preserving Mesh Denoising

In recent years researchers have made noticeable progresses in mesh denoising, that is, recovering high-quality 3D models from meshes corrupted with noise (raw or synthetic). Nevertheless, these state of the art approaches still fall short for robustly handling various noisy 3D models. The main tech...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 22(2016), 3 vom: 17. März, Seite 1181-94
1. Verfasser: Lu, Xuequan (VerfasserIn)
Weitere Verfasser: Deng, Zhigang, Chen, Wenzhi
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.
LEADER 01000naa a22002652 4500
001 NLM254780717
003 DE-627
005 20231224173118.0
007 cr uuu---uuuuu
008 231224s2016 xx |||||o 00| ||eng c
024 7 |a 10.1109/TVCG.2015.2500222  |2 doi 
028 5 2 |a pubmed24n0849.xml 
035 |a (DE-627)NLM254780717 
035 |a (NLM)26584492 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Lu, Xuequan  |e verfasserin  |4 aut 
245 1 2 |a A Robust Scheme for Feature-Preserving Mesh Denoising 
264 1 |c 2016 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 24.10.2016 
500 |a Date Revised 30.12.2016 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a In recent years researchers have made noticeable progresses in mesh denoising, that is, recovering high-quality 3D models from meshes corrupted with noise (raw or synthetic). Nevertheless, these state of the art approaches still fall short for robustly handling various noisy 3D models. The main technical challenge of robust mesh denoising is to remove noise while maximally preserving geometric features. In particular, this issue becomes more difficult for models with considerable amount of noise. In this paper we present a novel scheme for robust feature-preserving mesh denoising. Given a noisy mesh input, our method first estimates an initial mesh, then performs feature detection, identification and connection, and finally, iteratively updates vertex positions based on the constructed feature edges. Through many experiments, we show that our approach can robustly and effectively denoise various input mesh models with synthetic noise or raw scanned noise. The qualitative and quantitative comparisons between our method and the selected state of the art methods also show that our approach can noticeably outperform them in terms of both quality and robustness 
650 4 |a Journal Article 
650 4 |a Research Support, N.I.H., Extramural 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Research Support, U.S. Gov't, Non-P.H.S. 
700 1 |a Deng, Zhigang  |e verfasserin  |4 aut 
700 1 |a Chen, Wenzhi  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on visualization and computer graphics  |d 1996  |g 22(2016), 3 vom: 17. März, Seite 1181-94  |w (DE-627)NLM098269445  |x 1941-0506  |7 nnns 
773 1 8 |g volume:22  |g year:2016  |g number:3  |g day:17  |g month:03  |g pages:1181-94 
856 4 0 |u http://dx.doi.org/10.1109/TVCG.2015.2500222  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 22  |j 2016  |e 3  |b 17  |c 03  |h 1181-94