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A Dense Statistical Model of Facial Soft Tissue Thickness

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dc.contributor.authorGietzen, Thomas
dc.contributor.authorBrylka, Robert
dc.contributor.authorSchwanecke, Ulrich
dc.contributor.authorSchömer, Elmar
dc.contributor.editorEibl, Maximilian
dc.contributor.editorGaedke, Martin
dc.date.accessioned2017-08-28T23:49:25Z
dc.date.available2017-08-28T23:49:25Z
dc.date.issued2017
dc.description.abstractAmbient intelligence become more and more ubiquitous and help people achieving a more natural interaction with their electronically enhanced environment. One vital natural interface between humans and ambient intelligence are embodied conversational agents. Thereby, the acceptance of these virtual characters is all the greater, the more natural they look and behave. Since humans pay particular attention to the face, a natural-looking animation of the face is very important. In this paper we present a dense statistical model of facial soft tissue thickness that can be used to build accurate physics-based facial animations. The presented model not only can help to generate more natural facial animations of virtual characters but also can be used in other research domains such as forensic anthropology or medicine. Especially in the field of dentistry and orthodontics in particularly younger people and children are increasingly examined using X-ray technology. Thereby more and more volumetric images are generated, which further increase cost as well as the induced radiation dose. Here, for example, our statistical model can provide the basis for a new volumetric reconstruction process of a human’s facial bones in a cost-effective manner and with low radiation exposure.en
dc.identifier.doi10.18420/in2017_90
dc.identifier.isbn978-3-88579-669-5
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2017
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-275
dc.subject3D volume registration
dc.subjectambient intelligence
dc.subjectconversational agents
dc.subjectfacial soft tissue thickness
dc.subjectlateral cephalogram
dc.subjectmedical imaging
dc.subjectstatistical model
dc.titleA Dense Statistical Model of Facial Soft Tissue Thicknessen
gi.citation.endPage898
gi.citation.startPage891
gi.conference.date25.-29. September 2017
gi.conference.locationChemnitz
gi.conference.sessiontitleSENSYBLE – Smart Systems for Better Living Environments

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