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Conference Paper: Example-based hair geometry synthesis

TitleExample-based hair geometry synthesis
Authors
KeywordsDetail Transfer
Hair Clustering
Hair Modeling
Texture Synthesis
Vector Fields
Issue Date2009
Citation
Acm Transactions On Graphics, 2009, v. 28 n. 3 How to Cite?
AbstractWe present an example-based approach to hair modeling because creating hairstyles either manually or through image-based acquisition is a costly and time-consuming process. We introduce a hierarchical hair synthesis framework that views a hairstyle both as a 3D vector field and a 2D arrangement of hair strands on the scalp. Since hair forms wisps, a hierarchical hair clustering algorithm has been developed for detecting wisps in example hairstyles. The coarsest level of the output hairstyle is synthesized using traditional 2D texture synthesis techniques. Synthesizing finer levels of the hierarchy is based on cluster oriented detail transfer. Finally, we compute a discrete tangent vector field from the synthesized hair at every level of the hierarchy to remove undesired inconsistencies among hair trajectories. Improved hair trajectories can be extracted from the vector field. Based on our automatic hair synthesis method, we have also developed simple user-controlled synthesis and editing techniques including feature-preserving combing as well as detail transfer between different hairstyles. © 2009 ACM.
Persistent Identifierhttp://hdl.handle.net/10722/151955
ISSN
2023 Impact Factor: 7.8
2023 SCImago Journal Rankings: 7.766
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWang, Len_US
dc.contributor.authorYu, Yen_US
dc.contributor.authorZhou, Ken_US
dc.contributor.authorGuo, Ben_US
dc.date.accessioned2012-06-26T06:31:28Z-
dc.date.available2012-06-26T06:31:28Z-
dc.date.issued2009en_US
dc.identifier.citationAcm Transactions On Graphics, 2009, v. 28 n. 3en_US
dc.identifier.issn0730-0301en_US
dc.identifier.urihttp://hdl.handle.net/10722/151955-
dc.description.abstractWe present an example-based approach to hair modeling because creating hairstyles either manually or through image-based acquisition is a costly and time-consuming process. We introduce a hierarchical hair synthesis framework that views a hairstyle both as a 3D vector field and a 2D arrangement of hair strands on the scalp. Since hair forms wisps, a hierarchical hair clustering algorithm has been developed for detecting wisps in example hairstyles. The coarsest level of the output hairstyle is synthesized using traditional 2D texture synthesis techniques. Synthesizing finer levels of the hierarchy is based on cluster oriented detail transfer. Finally, we compute a discrete tangent vector field from the synthesized hair at every level of the hierarchy to remove undesired inconsistencies among hair trajectories. Improved hair trajectories can be extracted from the vector field. Based on our automatic hair synthesis method, we have also developed simple user-controlled synthesis and editing techniques including feature-preserving combing as well as detail transfer between different hairstyles. © 2009 ACM.en_US
dc.languageengen_US
dc.relation.ispartofACM Transactions on Graphicsen_US
dc.subjectDetail Transferen_US
dc.subjectHair Clusteringen_US
dc.subjectHair Modelingen_US
dc.subjectTexture Synthesisen_US
dc.subjectVector Fieldsen_US
dc.titleExample-based hair geometry synthesisen_US
dc.typeConference_Paperen_US
dc.identifier.emailYu, Y:yzyu@cs.hku.hken_US
dc.identifier.authorityYu, Y=rp01415en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1145/1531326.1531362en_US
dc.identifier.scopuseid_2-s2.0-70349659479en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70349659479&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume28en_US
dc.identifier.issue3en_US
dc.identifier.isiWOS:000269278000036-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridWang, L=35207052300en_US
dc.identifier.scopusauthoridYu, Y=8554163500en_US
dc.identifier.scopusauthoridZhou, K=7202915241en_US
dc.identifier.scopusauthoridGuo, B=7403276409en_US
dc.identifier.issnl0730-0301-

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