Bi-Normal Filtering for Mesh Denoising

Most mesh denoising techniques utilize only either the facet normal field or the vertex normal field of a mesh surface. The two normal fields, though contain some redundant geometry information of the same model, can provide additional information that the other field lacks. Thus, considering only o...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 21(2015), 1 vom: 10. Jan., Seite 43-55
1. Verfasser: Wei, Mingqiang (VerfasserIn)
Weitere Verfasser: Yu, Jinze, Pang, Wai-Man, Wang, Jun, Qin, Jing, Liu, Ligang, Heng, Pheng-Ann
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2015
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
LEADER 01000naa a22002652 4500
001 NLM252627636
003 DE-627
005 20231224164518.0
007 cr uuu---uuuuu
008 231224s2015 xx |||||o 00| ||eng c
024 7 |a 10.1109/TVCG.2014.2326872  |2 doi 
028 5 2 |a pubmed24n0842.xml 
035 |a (DE-627)NLM252627636 
035 |a (NLM)26357020 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Wei, Mingqiang  |e verfasserin  |4 aut 
245 1 0 |a Bi-Normal Filtering for Mesh Denoising 
264 1 |c 2015 
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 01.12.2015 
500 |a Date Revised 11.09.2015 
500 |a published: Print 
500 |a Citation Status PubMed-not-MEDLINE 
520 |a Most mesh denoising techniques utilize only either the facet normal field or the vertex normal field of a mesh surface. The two normal fields, though contain some redundant geometry information of the same model, can provide additional information that the other field lacks. Thus, considering only one normal field is likely to overlook some geometric features. In this paper, we take advantage of the piecewise consistent property of the two normal fields and propose an effective framework in which they are filtered and integrated using a novel method to guide the denoising process. Our key observation is that, decomposing the inconsistent field at challenging regions into multiple piecewise consistent fields makes the two fields complementary to each other and produces better results. Our approach consists of three steps: vertex classification, bi-normal filtering, and vertex position update. The classification step allows us to filter the two fields on a piecewise smooth surface rather than a surface that is smooth everywhere. Based on the piecewise consistence of the two normal fields, we filtered them using a piecewise smooth region clustering strategy. To benefit from the bi-normal filtering, we design a quadratic optimization algorithm for vertex position update. Experimental results on synthetic and real data show that our algorithm achieves higher quality results than current approaches on surfaces with multifarious geometric features and irregular surface sampling 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
700 1 |a Yu, Jinze  |e verfasserin  |4 aut 
700 1 |a Pang, Wai-Man  |e verfasserin  |4 aut 
700 1 |a Wang, Jun  |e verfasserin  |4 aut 
700 1 |a Qin, Jing  |e verfasserin  |4 aut 
700 1 |a Liu, Ligang  |e verfasserin  |4 aut 
700 1 |a Heng, Pheng-Ann  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on visualization and computer graphics  |d 1996  |g 21(2015), 1 vom: 10. Jan., Seite 43-55  |w (DE-627)NLM098269445  |x 1941-0506  |7 nnns 
773 1 8 |g volume:21  |g year:2015  |g number:1  |g day:10  |g month:01  |g pages:43-55 
856 4 0 |u http://dx.doi.org/10.1109/TVCG.2014.2326872  |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 21  |j 2015  |e 1  |b 10  |c 01  |h 43-55