DC FieldValueLanguage
dc.contributor.authorNtalianis, Klimis-
dc.contributor.authorKener, Andreas-
dc.contributor.authorKouremenos, Dimitris-
dc.date.accessioned2024-11-13T13:53:54Z-
dc.date.available2024-11-13T13:53:54Z-
dc.date.issued2023-06-
dc.identifiergoogle_scholar-vd7COBsAAAAJ:43bX7VzcjpAC-
dc.identifier.isbn978-981-19-5443-6-
dc.identifier.issn2194-5365-
dc.identifier.othervd7COBsAAAAJ:43bX7VzcjpAC-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2885-
dc.description.abstractSigning avatars make it possible for deaf people to access information in their preferred language. This paper describes the implementation of a new 3D high-realistic avatar, for Greek Sign Language (GSL) fingerspelling and numbering signs. This research study explores open-source 3D platforms such as MakeHuman, Blender, and Unity’s game engine as 3D rendering architectures. Creating signing virtual characters is important for training and communicating in virtual environments or further applications. This research looks at how to use the power of C# unity script code and layered motion game technology to achieve programmable transitions of animation segments and to create dynamical, real-time (on the fly), natural, and understandable outputs with controllable playback speed and playback views. Another novelty of the proposed scheme focuses on the precision of the transition time and how it blends between the last sign posture (first sign) and first sign posture animation (second sign).en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSentiment Analysis and Deep Learning: Proceedings of ICSADL 2022en_US
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computingen_US
dc.sourceSentiment Analysis and Deep Learning: Proceedings of ICSADL 2022, 843-858, 2023-
dc.subjectGreek Sign Languageen_US
dc.subjectGreek letters fingerspellingen_US
dc.subjectNumber gesture animationen_US
dc.subject3D Signing avataren_US
dc.title3D realistic animation of Greek Sign Language’s fingerspelled signsen_US
dc.typeBook Chapteren_US
dc.relation.conferenceInternational Conference on Sentimental Analysis and Deep Learning (ICSADL 2022), 16 - 17 June 2022, Thailanden_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.identifier.spage843en_US
dc.identifier.epage858en_US
dc.linkhttps://link.springer.com/chapter/10.1007/978-981-19-5443-6_63en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldSocial Sciencesen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusnot verifieden_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeBook Chapter-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου
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