基于GPU的图像拼接svd

2015 International Symposium on Computer Architecture and High Performance Computing Workshop (SBAC-PADW) Pub Date : 2015-10-18 DOI:10.1109/SBAC-PADW.2015.22

I. Badolato, Luciano de Paula, R. Farias

{"title":"基于GPU的图像拼接svd","authors":"I. Badolato, Luciano de Paula, R. Farias","doi":"10.1109/SBAC-PADW.2015.22","DOIUrl":null,"url":null,"abstract":"In this paper we present a homography algorithm to produce image mosaics using parallelism to solve a multiple Singular Value Decomposition (SVD) system. We analyse four state of art SVD methods and choose the one which better suites the expected size of the matrices derived from the datasets of interest. Then we use cuda to accelerate the solution of the transformation homogeneous matrices.","PeriodicalId":161685,"journal":{"name":"2015 International Symposium on Computer Architecture and High Performance Computing Workshop (SBAC-PADW)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Many SVDs on GPU for Image Mosaic Assemble\",\"authors\":\"I. Badolato, Luciano de Paula, R. Farias\",\"doi\":\"10.1109/SBAC-PADW.2015.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a homography algorithm to produce image mosaics using parallelism to solve a multiple Singular Value Decomposition (SVD) system. We analyse four state of art SVD methods and choose the one which better suites the expected size of the matrices derived from the datasets of interest. Then we use cuda to accelerate the solution of the transformation homogeneous matrices.\",\"PeriodicalId\":161685,\"journal\":{\"name\":\"2015 International Symposium on Computer Architecture and High Performance Computing Workshop (SBAC-PADW)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Symposium on Computer Architecture and High Performance Computing Workshop (SBAC-PADW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SBAC-PADW.2015.22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Symposium on Computer Architecture and High Performance Computing Workshop (SBAC-PADW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SBAC-PADW.2015.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

本文提出了一种利用并行性求解多重奇异值分解(SVD)系统生成图像拼接的单应性算法。我们分析了四种最先进的SVD方法，并选择了一种更好地适应从感兴趣的数据集导出的矩阵的期望大小的方法。然后利用cuda加速求解变换齐次矩阵。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Many SVDs on GPU for Image Mosaic Assemble

In this paper we present a homography algorithm to produce image mosaics using parallelism to solve a multiple Singular Value Decomposition (SVD) system. We analyse four state of art SVD methods and choose the one which better suites the expected size of the matrices derived from the datasets of interest. Then we use cuda to accelerate the solution of the transformation homogeneous matrices.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2015 International Symposium on Computer Architecture and High Performance Computing Workshop (SBAC-PADW)

自引率

0.00%

发文量