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2014 | OriginalPaper | Chapter

Affine SIFT Based on Particle Swarm Optimization

Authors : Xue-lian Cao, Guo-Rong Cai, Shui-li Chen

Published in: Fuzzy Information & Engineering and Operations Research & Management

Publisher: Springer Berlin Heidelberg

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Abstract

As for ASIFT, ASIFT has been proven to be invariant to image scaling and rotation. Specially, ASIFT enables matching of images with severe view point change and outperforms significantly the state-of-the-art methods. It accomplished this by simulating several views of the original images. However, we found that the simulated parameters are continuous, namely, transformations acquired by ASIFT cant express the real relationship between reference and input images. Therefore, a particle swarm optimization based sample strategy is presented in this paper. The basic idea is to search the best transform in continuous parameter space. Experimental results show that the proposed PSO-ASIFT algorithm could get more matches compared with the original ASIFT and SIFT.

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Metadata
Title
Affine SIFT Based on Particle Swarm Optimization
Authors
Xue-lian Cao
Guo-Rong Cai
Shui-li Chen
Copyright Year
2014
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-38667-1_7

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