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dc.contributor.authorÇipiloğlu Yıldız, Zeynep
dc.contributor.authorCapin, Tolga
dc.date.accessioned2020-07-02T07:23:27Z
dc.date.available2020-07-02T07:23:27Z
dc.date.issued2019
dc.identifier.isbn9789897583544
dc.identifier.urihttp://hdl.handle.net/20.500.12481/12275
dc.description.abstract3D mesh models are exposed to several geometric operations such as simplification and compression. Several metrics for evaluating the perceived quality of 3D meshes have already been developed. However, most of these metrics do not handle animation and they measure the global quality. Therefore, a full-reference perceptual error metric is proposed to estimate the detectability of local artifacts on animated meshes. This is a bottom-up approach in which spatial and temporal sensitivity models of the human visual system are integrated. The proposed method directly operates in 3D mode space and generates a 3D probability map that estimates the visibility of distortions on each vertex throughout the animation sequence. We have also tested the success of our metric on public datasets and compared the results to other metrics. These results reveal a promising correlation between our metric and human perception.tr_TR
dc.description.sponsorshipInstitute for Systems and Technologies of Information, Control and Communication (INSTICC)tr_TR
dc.language.isoentr_TR
dc.publisherSciTePresstr_TR
dc.rightsinfo:eu-repo/semantics/openAccesstr_TR
dc.subjectVisual quality assessmenttr_TR
dc.subjectAnimationtr_TR
dc.subjectGeometrytr_TR
dc.subjectContrast sensitivity functiontr_TR
dc.subjectManifold harmonicstr_TR
dc.titleA fully object-space approach for full-reference visual quality assessment of static and animated 3D meshestr_TR
dc.typeKonferans Ögesitr_TR
dc.contributor.MCBUauthorÇipiloğlu Yıldız, Zeynep
dc.contributor.departmentFakülteler > Mühendislik Fakültesi > Bilgisayar Mühendisliğitr_TR
dc.identifier.ORC-ID0000-0003-4129-591Xtr_TR
dc.identifier.categoryOfPublishedMaterialKonferans Öğesi - Ulusal - Kurum Öğretim Elemanıtr_TR
dc.identifier.nameOfPublishedMaterialVISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications Volume 1, 2019, Pages 169-176tr_TR
dc.identifier.DOI-ID10.5220/0007245001690176tr_TR
dc.identifier.indicesScopus (DOI)tr_TR


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