| 三维图像特征点匹配与拼接 |
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| 引用本文： | 陈守文,马姝婧,刘春昊,张淳奕.三维图像特征点匹配与拼接[J].化工进展,2018,37(Z1):223-228. |
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| 作者姓名： | 陈守文 马姝婧 刘春昊 张淳奕 |
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| 作者单位： | 中海油信息科技有限公司, 天津 300452 |
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| 摘 要： | 随着三维图像在生活中的广泛应用，三维图像处理技术逐渐成为研究的热点。不同的三维图像匹配技术在不同的应用领域具有各自的优点及不足。本文基于对几种主要的三维图像拼接算法如迭代最近点算法（ICP）、穷举搜索算法、标准化匹配算法、Spin Images描述算子及积分卷机描述算子的分析，提出了一些相应的优化方法，可为相关学者提供参考。
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| 关 键 词： | 三维图像 图像匹配 迭代最近点算法 特征点 |
| 收稿时间： | 2016-12-29 |
3D images' feature point and matching |
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| CHEN Shouwen,MA Shujing,LIU Chunhao,ZHANG Chunyi.3D images' feature point and matching[J].Chemical Industry and Engineering Progress,2018,37(Z1):223-228. |
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| Authors: | CHEN Shouwen MA Shujing LIU Chunhao ZHANG Chunyi |
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| Affiliation: | CNOOC Information Technology Co., Ltd., TianJin 300452, China |
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| Abstract: | 3D images are widely used in our lives, and the tech of 3D images processing is what people look for. Therefore, algorithm about registration of 3D images comes in sight. And different three-dimensional image matching technology has its own advantages and disadvantages corresponding to different application fields and use methods. This paper introduces some main important ways of 3D images matching and look ahead to its future. |
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| Keywords: | 3D images image matching ICP feature point |
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