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https://doi.org/10.1109/aisp.2...
Article . 2017 . Peer-reviewed
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Quick sift(QSIFT), an approach to reduce SIFT computational cost

Authors: Fazel, Zahra; Famouri, Mahmoud; Nazemi, Azadeh; Azimifar, Zohreh;

Quick sift(QSIFT), an approach to reduce SIFT computational cost

Abstract

SIFT has been proven to be the most robust local rotation and illumination invariant feature descriptor. Being fully scale invariant is the most important advantage of this descriptor. The major drawback of SIFT is time complexity which prevents utilizing SIFT in real-time applications. This paper describes a method to increase the speed of SIFT feature extraction using keypoint estimation and approximation instead of keypoint calculation in various scales. This research attempts to decrease SIFT computational cost without sacrificing performance and propose quick SIFT method (QSIFT). The recent researches in this area have approved that direct feature value computation is more expensive than the value extrapolation. Consequently, the contribution of this research is to reduces the time execution without losing accuracy.

Country
Ireland
Related Organizations
Keywords

Signal processing, Feature matching, Feature detector, natural image statistics, real-time, Cameras, Computational efficiency, Time complexity, Feature extraction, Feature descriptor, Real-time systems, Interest points, Lighting

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green