Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Method for Generating Panoramic Textures for 3D Face Reconstruction Based on the 3D Morphable Model

Full metadata record
DC Field Value Language
dc.contributor.authorHao, Shujia-
dc.contributor.authorWen, Mingyun-
dc.contributor.authorCho, Kyungeun-
dc.date.accessioned2023-04-27T09:40:35Z-
dc.date.available2023-04-27T09:40:35Z-
dc.date.issued2022-10-
dc.identifier.issn2076-3417-
dc.identifier.issn2076-3417-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/2502-
dc.description.abstractThree-dimensional (3D) reconstruction techniques are playing an increasingly important role in education and entertainment. Real and recognizable avatars can enhance the immersion and interactivity of virtual systems. In 3D face modeling technology, face texture carries vital face recognition information. Therefore, this study proposes a panoramic 3D face texture generation method for 3D face reconstruction from a single 2D face image based on a 3D Morphable model (3DMM). Realistic and comprehensive panoramic facial textures can be obtained using generative networks as texture converters. Furthermore, we propose a low-cost method for generating face texture datasets for data collection. Experimental results show that the proposed method can generate panoramic face textures for 3D face meshes from a single image input, resulting in the final generation of textured 3D models that look realistic from different viewpoints.-
dc.format.extent19-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleMethod for Generating Panoramic Textures for 3D Face Reconstruction Based on the 3D Morphable Model-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/app121910020-
dc.identifier.scopusid2-s2.0-85139944777-
dc.identifier.wosid000866594600001-
dc.identifier.bibliographicCitationApplied Sciences, v.12, no.19, pp 1 - 19-
dc.citation.titleApplied Sciences-
dc.citation.volume12-
dc.citation.number19-
dc.citation.startPage1-
dc.citation.endPage19-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryChemistry, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryEngineering, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.subject.keywordAuthorpanoramic texture generation-
dc.subject.keywordAuthordeep learning-
dc.subject.keywordAuthoradversarial learning-
dc.subject.keywordAuthorimage translation-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

qrcode

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

Related Researcher

Researcher Cho, Kyung Eun photo

Cho, Kyung Eun
College of Advanced Convergence Engineering (Department of Computer Science and Artificial Intelligence)
Read more

Altmetrics

Total Views & Downloads

BROWSE