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dc.contributor.authorLiu, T.
dc.contributor.authorTai, C.
dc.contributor.authorZhu, Maggie
dc.contributor.authorBagchi, J.
dc.contributor.authorAllebach, J.
dc.date.accessioned2018-08-08T04:43:52Z
dc.date.available2018-08-08T04:43:52Z
dc.date.created2018-08-08T03:50:50Z
dc.date.issued2017
dc.identifier.citationLiu, T. and Tai, C. and Zhu, M. and Bagchi, J. and Allebach, J. 2017. Texture re-rendering tool for re-mixing indoor scene images, pp. 86-92.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/70209
dc.identifier.doi10.2352/ISSN.2470-1173.2017.10.IMAWM-177
dc.description.abstract

© 2017, Society for Imaging Science and Technology. We propose a novel tool for re-rendering objects in indoor scene images with new textures. It aims to address the problem of too much manual work of positioning and alignment when applying new texture onto an object surface in an indoor scene image. The algorithm of the tool is based on establishing 2D projective transformation between texture images and planar object surfaces in scene images. In order to find the transformation, we use a sampled rectangular texture pattern from a large synthesized planar texture and a planar quadrangle corresponding to object surface orientation estimation, which is generated by a geometric orientation hypothesis framework. The tool also puts effort in adjusting the scaling and reducing artifacts for re-rendered textures. We present the re-rendering results for ceilings, walls, floors, etc. that naturally correspond to room geometry layout.

dc.titleTexture re-rendering tool for re-mixing indoor scene images
dc.typeConference Paper
dcterms.source.startPage86
dcterms.source.endPage92
dcterms.source.issn2470-1173
dcterms.source.titleIS and T International Symposium on Electronic Imaging Science and Technology
dcterms.source.seriesIS and T International Symposium on Electronic Imaging Science and Technology
curtin.departmentSchool of Public Health
curtin.accessStatusFulltext not available


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