中文摘要：

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。

英文摘要：

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.