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dc.contributor.author 天目, 隆平 ja
dc.contributor.author 神原, 誠之 ja
dc.contributor.author 横矢, 直和 ja
dc.date.accessioned 2016-11-08T07:20:23Z en
dc.date.available 2016-11-08T07:20:23Z en
dc.date.issued 2005-09-30 en
dc.identifier.issn 1344-011X en
dc.identifier.uri http://hdl.handle.net/10061/11088 en
dc.description.abstract By realizing augmented reality on wearable computers, it becomes possible to overlay annotations on the real world based on user's current position and orientation. However, it is difficult for the user to understand links between annotations and real objects intuitively when the scene is complicated or many annotations are overlaid at the same time. This paper describes a view management method which emphasizes user's gazed real objects and their annotations using 3D models of the scene. The proposed method effectively highlights the objects gazed by the user. In addition, when the gazed object is occluded by other real objects, the object is complemented by using an image, which is made from 3D models, on the overlaid image. en
dc.language.iso ja en
dc.publisher 日本バーチャルリアリティ学会 ja
dc.rights Copyright c 2005 特定非営利活動法人日本バーチャルリアリティ学会 ja
dc.subject wearable computer en
dc.subject augmented reality en
dc.subject view management en
dc.subject annotation en
dc.subject 3D model en
dc.title ウェアラブル拡張現実感システムのための注目オブジェクトへの直感的な注釈提示手法 ja
dc.title.alternative Intuitively Annotating A User's Gazed Object for Wearable AR Systems en
dc.type.nii Journal Article en
dc.contributor.transcription テンモク, リュウヘイ ja
dc.contributor.transcription カンバラ, マサユキ ja
dc.contributor.transcription ヨコヤ, ナオカズ ja
dc.contributor.alternative Tenmoku, Ryuhei en
dc.contributor.alternative Kanbara, Masayuki en
dc.contributor.alternative Yokoya, Naokazu en
dc.textversion Publisher en
dc.identifier.ncid AA11448578 en
dc.identifier.jtitle 日本バーチャルリアリティ学会論文誌 ja
dc.identifier.volume 10 en
dc.identifier.issue 3 en
dc.identifier.spage 305 en
dc.identifier.epage 311 en
dc.relation.doi 10.18974/tvrsj.10.3_305 en
dc.identifier.NAIST-ID 73292542 en
dc.identifier.NAIST-ID 73292286 en

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