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This paper proposes a novel strength correspondence weighted graph for multi-scale image registration. First, the strength correspondence weighted graph is proposed based on the structure information and attributes relations of graph. Second, a similarity scale parameter obtained which can adjust adaptively scale based on the similarity of the different feature points. Third, the energy is embedded...
The problem of point pattern matching (PPM) is frequently encountered in computer vision, such as image registration and image matching. This paper investigates the manifold approaches to the problem of point pattern matching, and proposes a manifold correspondence based on Locally Linear Embedding (LLE). Our method operates on embeddings of the two data sets in the manifold space so as to get embedding...
This paper proposes a novel feature descriptor - locality preserving descriptor to the problem of point pattern matching. The idea behind a locality preserving is to map points that are nearby in the data space into points that are nearby in the feature space. The feature descriptor optimally preserves the neighborhood structure of the data set, and is invariant to translation, scale, and rotation...
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