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dc.contributor.authorSu, Rung-Deen_US
dc.contributor.authorLiao, Zhe-Yoen_US
dc.contributor.authorChen, Li-Chien_US
dc.contributor.authorTung, Ai-Lingen_US
dc.contributor.authorWang, Yu-Shuenen_US
dc.date.accessioned2020-02-02T23:54:38Z-
dc.date.available2020-02-02T23:54:38Z-
dc.date.issued2019-10-01en_US
dc.identifier.issn0167-7055en_US
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.13823en_US
dc.identifier.urihttp://hdl.handle.net/11536/153585-
dc.description.abstractSelecting informative and visually appealing views for 3D indoor scenes is beneficial for the housing, decoration, and entertainment industries. A set of views that exhibit comfort, aesthetics, and functionality of a particular scene can attract customers and facilitate business transactions. However, selecting views for an indoor scene is challenging because the system has to consider not only the need to reveal as much information as possible, but also object arrangements, occlusions, and characteristics. Since there can be many principles utilized to guide the view selection, and various principles to follow under different circumstances, we achieve the goal by imitating popular photos on the Internet. Specifically, we select the view that can optimize the contour similarity of corresponding objects to the photo. Because the selected view can be inadequate if object arrangements in the 3D scene and the photo are different, our system imitates many popular photos and selects a certain number of views. After that, it clusters the selected views and determines the view/cluster centers by the weighted average to finally exhibit the scene. Experimental results demonstrate that the views selected by our method are visually appealing.en_US
dc.language.isoen_USen_US
dc.titleImitating Popular Photos to Select Views for an Indoor Sceneen_US
dc.typeArticleen_US
dc.identifier.doi10.1111/cgf.13823en_US
dc.identifier.journalCOMPUTER GRAPHICS FORUMen_US
dc.citation.volume38en_US
dc.citation.issue7en_US
dc.citation.spage141en_US
dc.citation.epage148en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.identifier.wosnumberWOS:000496351100013en_US
dc.citation.woscount0en_US
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