利用立体摄像机对室内物体进行三维重建与测量

Wei Ma, M. Le, K. Jo
{"title":"利用立体摄像机对室内物体进行三维重建与测量","authors":"Wei Ma, M. Le, K. Jo","doi":"10.1109/IFOST.2011.6021128","DOIUrl":null,"url":null,"abstract":"This paper implements a study of 3D reconstruction and measurement of indoor objects using binocular stereo camera. First, SIFT feature are extracted from both images and the matching points are found. RANSAC method is applied to eliminate wrong matching points. Second, two stereo images are rectified and generated disparity mapping. Finally, the depth mapping and 3D information of each pixel are derived. This method is applied to reconstruct and measure the true object in indoor environment.","PeriodicalId":20466,"journal":{"name":"Proceedings of 2011 6th International Forum on Strategic Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"3D reconstruction and measurement of indoor object using stereo camera\",\"authors\":\"Wei Ma, M. Le, K. Jo\",\"doi\":\"10.1109/IFOST.2011.6021128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper implements a study of 3D reconstruction and measurement of indoor objects using binocular stereo camera. First, SIFT feature are extracted from both images and the matching points are found. RANSAC method is applied to eliminate wrong matching points. Second, two stereo images are rectified and generated disparity mapping. Finally, the depth mapping and 3D information of each pixel are derived. This method is applied to reconstruct and measure the true object in indoor environment.\",\"PeriodicalId\":20466,\"journal\":{\"name\":\"Proceedings of 2011 6th International Forum on Strategic Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2011 6th International Forum on Strategic Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IFOST.2011.6021128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2011 6th International Forum on Strategic Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IFOST.2011.6021128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

本文对利用双目立体摄像机对室内物体进行三维重建与测量进行了研究。首先,对两幅图像提取SIFT特征,找到匹配点;采用RANSAC方法消除错误匹配点。其次,对两幅立体图像进行校正,生成视差映射;最后,导出深度映射和每个像素的三维信息。该方法适用于室内环境下真实物体的重建和测量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D reconstruction and measurement of indoor object using stereo camera
This paper implements a study of 3D reconstruction and measurement of indoor objects using binocular stereo camera. First, SIFT feature are extracted from both images and the matching points are found. RANSAC method is applied to eliminate wrong matching points. Second, two stereo images are rectified and generated disparity mapping. Finally, the depth mapping and 3D information of each pixel are derived. This method is applied to reconstruct and measure the true object in indoor environment.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信