通过最小比率循环紧凑窗口的立体匹配

O. Veksler
{"title":"通过最小比率循环紧凑窗口的立体匹配","authors":"O. Veksler","doi":"10.1109/ICCV.2001.937563","DOIUrl":null,"url":null,"abstract":"Window size and shape selection is a difficult problem in area based stereo. We propose an algorithm which chooses an appropriate window shape by optimizing over a large class of \"compact\" windows. We call them compact because their ratio of perimeter to area tends to be small. We believe that this is the first window matching algorithm which can explicitly construct non-rectangular windows. Efficient optimization over the compact window class is achieved via the minimum ratio cycle algorithm. In practice it takes time linear in the size of the largest window in our class. Still the straightforward approach to find the optimal window for each pixel-disparity pair is too slow. We develop pruning heuristics which gave practically the same results while reducing running time from minutes to seconds. Our experiments show that unlike fixed window algorithms, our method avoids blurring disparity boundaries as well as constructs large windows in low textured areas. The algorithm has few parameters which are easy to choose, and the same parameters work well for different image pairs.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"98","resultStr":"{\"title\":\"Stereo matching by compact windows via minimum ratio cycle\",\"authors\":\"O. Veksler\",\"doi\":\"10.1109/ICCV.2001.937563\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Window size and shape selection is a difficult problem in area based stereo. We propose an algorithm which chooses an appropriate window shape by optimizing over a large class of \\\"compact\\\" windows. We call them compact because their ratio of perimeter to area tends to be small. We believe that this is the first window matching algorithm which can explicitly construct non-rectangular windows. Efficient optimization over the compact window class is achieved via the minimum ratio cycle algorithm. In practice it takes time linear in the size of the largest window in our class. Still the straightforward approach to find the optimal window for each pixel-disparity pair is too slow. We develop pruning heuristics which gave practically the same results while reducing running time from minutes to seconds. Our experiments show that unlike fixed window algorithms, our method avoids blurring disparity boundaries as well as constructs large windows in low textured areas. The algorithm has few parameters which are easy to choose, and the same parameters work well for different image pairs.\",\"PeriodicalId\":429441,\"journal\":{\"name\":\"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"98\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCV.2001.937563\",\"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 Eighth IEEE International Conference on Computer Vision. ICCV 2001","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2001.937563","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 98

摘要

窗口大小和形状的选择是基于区域立体的难点问题。我们提出了一种算法,该算法通过优化一大类“紧凑”窗口来选择合适的窗口形状。我们称它们为紧凑型是因为它们的周长与面积之比很小。我们认为这是第一个可以显式构造非矩形窗口的窗口匹配算法。通过最小比率循环算法实现了紧凑窗口类的有效优化。在实践中,我们班最大的窗口的大小是线性的。但是,为每个像素差对找到最佳窗口的直接方法太慢了。我们开发了剪枝启发式算法,它在将运行时间从几分钟缩短到几秒钟的同时,几乎给出了相同的结果。实验表明,与固定窗口算法不同,该方法避免了视差边界的模糊,并在低纹理区域构建了大窗口。该算法参数少,易于选择,且相同的参数对不同的图像对都能很好地匹配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stereo matching by compact windows via minimum ratio cycle
Window size and shape selection is a difficult problem in area based stereo. We propose an algorithm which chooses an appropriate window shape by optimizing over a large class of "compact" windows. We call them compact because their ratio of perimeter to area tends to be small. We believe that this is the first window matching algorithm which can explicitly construct non-rectangular windows. Efficient optimization over the compact window class is achieved via the minimum ratio cycle algorithm. In practice it takes time linear in the size of the largest window in our class. Still the straightforward approach to find the optimal window for each pixel-disparity pair is too slow. We develop pruning heuristics which gave practically the same results while reducing running time from minutes to seconds. Our experiments show that unlike fixed window algorithms, our method avoids blurring disparity boundaries as well as constructs large windows in low textured areas. The algorithm has few parameters which are easy to choose, and the same parameters work well for different image pairs.
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:604180095
Book学术官方微信