{"title":"A GPU-based framework of photometric uniformity for multi-projector tiled display","authors":"Guodong Yuan, K. Qin","doi":"10.2312/EGVE/IPT_EGVE2007/077-083","DOIUrl":null,"url":null,"abstract":"In this paper, we firstly propose a partial-sampling scheme to measure the intensity transfer function of a projector. Secondly, we implement the computation of luminance surface by rendering a texture rectangle on GPU. Thirdly, we generate an unified index data for all projectors. And then we compute the masks of photometric correction using a GPU based on topological consistency. Finally we integrate the masks with a GPU-based photometric correction pipeline to achieve the photometric uniformity for multi-projector display. The GPU-based framework is a combination of the GPU-based computation and the GPU-based photometric correction pipeline, which removes the bottleneck of the computation of luminance surface, attenuation mask and black offset mask. It is shown by experimental results prove that the GPU-based framework is effective and efficient.","PeriodicalId":210571,"journal":{"name":"International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2007-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/EGVE/IPT_EGVE2007/077-083","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we firstly propose a partial-sampling scheme to measure the intensity transfer function of a projector. Secondly, we implement the computation of luminance surface by rendering a texture rectangle on GPU. Thirdly, we generate an unified index data for all projectors. And then we compute the masks of photometric correction using a GPU based on topological consistency. Finally we integrate the masks with a GPU-based photometric correction pipeline to achieve the photometric uniformity for multi-projector display. The GPU-based framework is a combination of the GPU-based computation and the GPU-based photometric correction pipeline, which removes the bottleneck of the computation of luminance surface, attenuation mask and black offset mask. It is shown by experimental results prove that the GPU-based framework is effective and efficient.