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Dense Correspondence Through Descriptor Matching

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Indexed by:Journal Papers

Date of Publication:2012-05-01

Journal:Journal of Information and Computational Science

Included Journals:EI、Scopus

Volume:9

Issue:5

Page Number:1135-1143

ISSN No.:15487741

Abstract:Image alignment is a very important task in image processing. In this paper, we focus on the dense correspondence to deal with drastic changes and large displacement existing in the images. We introduce the more robust feature descriptor as the representation of the raw image pixel combining the optical flow model to build the correspondence. According to the statistical properties of dense descriptors, we propose robust function to reject outliers. In order to deal with occlusions, we propose a new method based on the robust regularization term which combines the varying support weight. The effectiveness of our method is borne out by abundant experiments.

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