一种用于寻找玻璃的测地线主动轮廓框架

Kenton McHenry, J. Ponce
{"title":"一种用于寻找玻璃的测地线主动轮廓框架","authors":"Kenton McHenry, J. Ponce","doi":"10.1109/CVPR.2006.28","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of finding objects made of glass (or other transparent materials) in images. Since the appearance of glass objects depends for the most part on what lies behind them, we propose to use binary criteria (\"are these two regions made of the same material?\") rather than unary ones (\"is this glass?\") to guide the segmentation process. Concretely, we combine two complementary measures of affinity between regions made of the same material and discrepancy between regions made of different ones into a single objective function, and use the geodesic active contour framework to minimize this function over pixel labels. The proposed approach has been implemented, and qualitative and quantitative experimental results are presented.","PeriodicalId":421737,"journal":{"name":"2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":"{\"title\":\"A Geodesic Active Contour Framework for Finding Glass\",\"authors\":\"Kenton McHenry, J. Ponce\",\"doi\":\"10.1109/CVPR.2006.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the problem of finding objects made of glass (or other transparent materials) in images. Since the appearance of glass objects depends for the most part on what lies behind them, we propose to use binary criteria (\\\"are these two regions made of the same material?\\\") rather than unary ones (\\\"is this glass?\\\") to guide the segmentation process. Concretely, we combine two complementary measures of affinity between regions made of the same material and discrepancy between regions made of different ones into a single objective function, and use the geodesic active contour framework to minimize this function over pixel labels. The proposed approach has been implemented, and qualitative and quantitative experimental results are presented.\",\"PeriodicalId\":421737,\"journal\":{\"name\":\"2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"41\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.2006.28\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.2006.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41

摘要

本文解决了在图像中寻找由玻璃(或其他透明材料)制成的物体的问题。由于玻璃物体的外观在很大程度上取决于它们背后的东西,我们建议使用二元标准(“这两个区域是由相同的材料制成的吗?”)而不是一元标准(“这是玻璃吗?”)来指导分割过程。具体而言,我们将相同材料区域之间的亲和力和不同材料区域之间的差异这两个互补的度量结合到一个单一的目标函数中,并使用测地线活动轮廓框架在像素标签上最小化该函数。所提出的方法已经实现,并给出了定性和定量的实验结果。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Geodesic Active Contour Framework for Finding Glass
This paper addresses the problem of finding objects made of glass (or other transparent materials) in images. Since the appearance of glass objects depends for the most part on what lies behind them, we propose to use binary criteria ("are these two regions made of the same material?") rather than unary ones ("is this glass?") to guide the segmentation process. Concretely, we combine two complementary measures of affinity between regions made of the same material and discrepancy between regions made of different ones into a single objective function, and use the geodesic active contour framework to minimize this function over pixel labels. The proposed approach has been implemented, and qualitative and quantitative experimental results are presented.
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
期刊最新文献
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image Efficient Maximally Stable Extremal Region (MSER) Tracking Transformation invariant component analysis for binary images Region-Tree Based Stereo Using Dynamic Programming Optimization Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1