A real-time implementation of SIFT using GPU

Acharya, Aniruddha K and Babu, RV and Vadhiyar, Sathish S (2018) A real-time implementation of SIFT using GPU. In: JOURNAL OF REAL-TIME IMAGE PROCESSING, 14 (2). pp. 267-277.

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Abstract

Scale-Invariant Feature Transform (SIFT) is one of the widely used interest point features. It has been successfully applied in various computer vision algorithms like object detection, object tracking, robotic mapping and large-scale image retrieval. Although SIFT descriptors are highly robust towards scale and rotation variations, the high computational complexity of the SIFT algorithm inhibits its use in applications demanding real-time response, and in algorithms dealing with very large-scale databases. This paper presents a parallel implementation of SIFT on a GPU, where we obtain a speed of around 55 fps for a 640 x 480 image. One of the main contributions of our work is the novel combined kernel optimization that has led to a significant improvement of 12.2 % in the execution speed. We compare our results with the existing SIFT implementations in the literature, and find that our implementation has better speedup than most of them.

Item Type:	Journal Article
Publication:	JOURNAL OF REAL-TIME IMAGE PROCESSING
Publisher:	SPRINGER HEIDELBERG, TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
Additional Information:	Copy right for the article belong to SPRINGER HEIDELBERG, TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY
Department/Centre:	Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	13 Apr 2018 19:58
Last Modified:	25 Feb 2019 05:50
URI:	http://eprints.iisc.ac.in/id/eprint/59536

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