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2013 | OriginalPaper | Chapter

57. Fast SIFT Algorithm Using Recursive Gaussian Filters

Authors : Zhengyuan Ye, Shouxun Liu, Xuan Wang

Published in: Proceedings of 2013 Chinese Intelligent Automation Conference

Publisher: Springer Berlin Heidelberg

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Abstract

Scale invariant feature transform (SIFT) algorithm has drawn great attention from computer vision engineers since it was proposed in 1999. However, the high computational complexity of the algorithm has hindered its application. In this paper, a fast SIFT algorithm is proposed, in which FIR Gaussian filters are replaced by recursive filters. Experimental results show that the proposed fast SIFT method needs less computation and yields nearly the same performance compares to original method. It is also recognized that the impulse response approximation error can be used as a good measure to estimate performance degradation of SIFT algorithm in recursive Gaussian filters. Furthermore, through using recursive filters, more choices of the values of prior smoothing scale can be made without considering the number of operations.

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Metadata
Title
Fast SIFT Algorithm Using Recursive Gaussian Filters
Authors
Zhengyuan Ye
Shouxun Liu
Xuan Wang
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
Book
Proceedings of 2013 Chinese Intelligent Automation Conference

Print ISBN: 978-3-642-38465-3

Electronic ISBN: 978-3-642-38466-0

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-642-38466-0_57