liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Face detection for selective polygon reduction of humanoid meshes
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Automatic mesh optimization algorithms suffer from the problem that humans are not uniformly sensitive to changes on different parts of the body. This is a problem because when a mesh optimization algorithm typically measures errors caused by triangle reductions, the errors are strictly geometrical, and an error of a certain magnitude on the thigh of a 3D model will be perceived by a human as less of an error than one of equal geometrical significance introduced on the face. The partial solution to this problem proposed in this paper consists of detecting the faces of the 3D assets to be optimized using conventional, existing 2D face detection algorithms, and then using this information to selectively and automatically preserve the faces of 3D assets that are to be optimized, leading to a smaller perceived error in the optimized model, albeit not necessarily a smaller geometrical error. This is done by generating a set of per-vertex weights that are used to scale the errors measured by the reduction algorithm, hence preserving areas with higher weights. The final optimized meshes produced by using this method is found to be subjectively closer to the original 3D asset than their non-weighed counterparts, and if the input meshes conform to certain criteria this method is well suited for inclusion in a fully automatic mesh decimation pipeline

Place, publisher, year, edition, pages
2015. , 26 p.
Keyword [en]
mesh, reduction, decimation
National Category
Media and Communication Technology
URN: urn:nbn:se:liu:diva-119967ISRN: LIU-ITN-TEK-A--15/038--SEOAI: diva2:838720
Subject / course
Media Technology
Available from: 2015-07-01 Created: 2015-07-01 Last updated: 2015-07-01Bibliographically approved

Open Access in DiVA

fulltext(1423 kB)100 downloads
File information
File name FULLTEXT01.pdfFile size 1423 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Henriksson, Johan
By organisation
Media and Information TechnologyThe Institute of Technology
Media and Communication Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 100 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 118 hits
ReferencesLink to record
Permanent link

Direct link