SIFT and it’s Variants: An Overview

7 Pages Posted: 14 Jun 2019

See all articles by Hima Bindu Chelluri

Hima Bindu Chelluri

GITAM (Deemed to be university)

K Manjunathachari

GITAM (Deemed to be University)

Date Written: February 2019

Abstract

SIFT is a powerful feature description algorithm in the field of computer vision and pattern recognition. It finds its application in many real-world applications like object recognition, image retrieval, image matching,etc. due to its numerous robust properties. Since its inception, researchers are trying to improvise it in many ways and as a result, many variants of SIFT came into existence. In computer vision and pattern recognition literature, there are a good amount of reviews articles available on the earliest variants of SIFT like PCA-SIFT, SURF, etc. However,very limited literature is available that reviewed the latest variants. This paper comprehensively reviews some of the state of the art variants in SIFT family along with the popular old variants. It discusses the drawbacks in SIFT and how these drawbacks paved the way for the existence of different variants. A detailed description of each variant is presented and concluded with its pros and cons. The different variants reviewed in the paper are PCA-SIFT, SURF, GSIFT, CSIFT, ASIFT, VF-SIFT, and DSIFT.

Suggested Citation

Chelluri, Hima Bindu and Manjunathachari, K, SIFT and it’s Variants: An Overview (February 2019). Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur - India, February 26-28, 2019. Available at SSRN: https://ssrn.com/abstract=3358743 or http://dx.doi.org/10.2139/ssrn.3358743

Hima Bindu Chelluri (Contact Author)

GITAM (Deemed to be university) ( email )

Rudraram
Sangareddy

K Manjunathachari

GITAM (Deemed to be University) ( email )

Rudraram
Sangareddy

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