C. Andújar, O. Argudo, I. Besora, P. Brunet, A. Chica, Marc Comino
{"title":"建筑重建的深度图修复","authors":"C. Andújar, O. Argudo, I. Besora, P. Brunet, A. Chica, Marc Comino","doi":"10.2312/ceig.20181162","DOIUrl":null,"url":null,"abstract":"properties surface images from we present a simple method for detecting, classifying and filling non-valid data regions in depth maps produced by dense stereo algorithms. Triangles meshes reconstructed from our repaired depth maps exhibit much higher quality than those produced by state-of-the-art reconstruction algorithms like Screened Poisson-based techniques.","PeriodicalId":385751,"journal":{"name":"Spanish Computer Graphics Conference","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Depth Map Repairing for Building Reconstruction\",\"authors\":\"C. Andújar, O. Argudo, I. Besora, P. Brunet, A. Chica, Marc Comino\",\"doi\":\"10.2312/ceig.20181162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"properties surface images from we present a simple method for detecting, classifying and filling non-valid data regions in depth maps produced by dense stereo algorithms. Triangles meshes reconstructed from our repaired depth maps exhibit much higher quality than those produced by state-of-the-art reconstruction algorithms like Screened Poisson-based techniques.\",\"PeriodicalId\":385751,\"journal\":{\"name\":\"Spanish Computer Graphics Conference\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spanish Computer Graphics Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2312/ceig.20181162\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spanish Computer Graphics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/ceig.20181162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
properties surface images from we present a simple method for detecting, classifying and filling non-valid data regions in depth maps produced by dense stereo algorithms. Triangles meshes reconstructed from our repaired depth maps exhibit much higher quality than those produced by state-of-the-art reconstruction algorithms like Screened Poisson-based techniques.
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