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一种利用流形学习进行多影像匹配的方法 被引量：4

A Novel Method on Manifold for Multi-image Matching
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摘要 提出了一种利用流形学习方法进行多影像匹配的算法。通过两组宽基线序列影像的匹配实验,并与LE-SIFT方法、SVD-SIFT方法和基于局部线性映射的LLE-SVD方法进行了对比分析。结果表明,本文方法在获得多幅影像的共同匹配结果和利用多幅影像之间的约束实现两幅影像匹配的结果上都优于现有方法。 A novel algorithm for multi-image matching by using a manifold learning method is presented.The matching algorithm applies the Laplacian Eigenmap algorithm to map feature points from different images to the same embedding space.Meantime,the local and global distribution similarities of feature points are calculated by SIFT descriptor and location information.Finally,a series of carefully designed experiments on two groups of the wide-baseline image sequences are designed to demonstrate and validate the performance of the proposed algorithm,which is higher than that of the LE-SIFT,SVD-SIFT and LLE-SVD methods in multi-image matching and stereo matching under the multi-image constrains.
作者 李爱霞 关泽群 冯甜甜
机构地区 同济大学测量与国土信息工程系
出处 《武汉大学学报（信息科学版）》 EI CSCD 北大核心 2012年第11期1303-1306,1315,共5页 Geomatics and Information Science of Wuhan University
基金 国家自然科学基金资助项目(41171327) 同济大学人才基金资助项目(0200144055) 青年优秀人才培养行动计划资助项目(0250219047)
关键词 多影像匹配 流形学习 局部相似性 分布相似性 multi-image matching manifold learning local similarity distribution similarity
分类号 P237.3 [天文地球—摄影测量与遥感]
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参考文献13

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二级参考文献14

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共引文献39

同被引文献35

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引证文献4

二级引证文献17

武汉大学学报（信息科学版）
2012年 第11期

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