{"title":"基于遗传算法的图像演练自适应采样","authors":"Dong Hoon Lee, Jong Ryul Kim, Soon Ki Jung","doi":"10.2312/EGVE/EGVE06/135-142","DOIUrl":null,"url":null,"abstract":"This paper presents an adaptive sampling method for image-based walkthrough. Our goal is to select minimal sets from the initially dense sampled data set, while guaranteeing a visual correct view from any position in any direction in walkthrough space. For this purpose we formulate the covered region for sampling criteria and then regard the sampling problem as a set covering problem. We estimate the optimal set using Genetic algorithm, and show the efficiency of the proposed method with several experiments.","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":"2006-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GA based adaptive sampling for image-based walkthrough\",\"authors\":\"Dong Hoon Lee, Jong Ryul Kim, Soon Ki Jung\",\"doi\":\"10.2312/EGVE/EGVE06/135-142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an adaptive sampling method for image-based walkthrough. Our goal is to select minimal sets from the initially dense sampled data set, while guaranteeing a visual correct view from any position in any direction in walkthrough space. For this purpose we formulate the covered region for sampling criteria and then regard the sampling problem as a set covering problem. We estimate the optimal set using Genetic algorithm, and show the efficiency of the proposed method with several experiments.\",\"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\":\"2006-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"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/EGVE06/135-142\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","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/EGVE06/135-142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GA based adaptive sampling for image-based walkthrough
This paper presents an adaptive sampling method for image-based walkthrough. Our goal is to select minimal sets from the initially dense sampled data set, while guaranteeing a visual correct view from any position in any direction in walkthrough space. For this purpose we formulate the covered region for sampling criteria and then regard the sampling problem as a set covering problem. We estimate the optimal set using Genetic algorithm, and show the efficiency of the proposed method with several experiments.