By the same authors

Feature Point Matching Using a Hermitian Property Matrix

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Title of host publicationSIMILARITY-BASED PATTERN RECOGNITION: FIRST INTERNATIONAL WORKSHOP, SIMBAD 2011
DatePublished - 2011
Pages321-332
Number of pages12
PublisherSPRINGER-VERLAG BERLIN
Place of PublicationBERLIN
EditorsM Pelillo, ER Hancock
Volume7005 LNCS
Original languageEnglish
ISBN (Print)978-3-642-24471-1

Abstract

This paper describes the computation of feature point correspondences using the spectra of a Hermitian property matrix. Firstly, a complex Laplacian (Hermitian) matrix is constructed from the Gaussian-weighted distances and the difference of SIFT [10] angles between each pair of points in the two images to be matched. Matches are computed by comparing the complex eigenvectors of the Hermitian property matrices for the two point sets acquired from the two images. Secondly, we embed the complex modal structure within Carcassoni's [12] iterative alignment method to render it more robust to rotation. Our method has been evaluated on both synthetic and real-world data.

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