Comparative Analysis of the Feature Extraction Performance of Augmented Reality Algorithms

Umut Tosun

doi:10.17776/csj.638297

EN

Comparative Analysis of the Feature Extraction Performance of Augmented Reality Algorithms

Abstract

The algorithms that extract keypoints and descriptors in augmented reality applications are getting more and more important in terms of performance. Criterions like time and correct matching of points gain more impact according to the type of application. In this paper, the performance of the algorithms used to identify an image using keypoint and descriptor extraction is studied. In the context of this research, main criterion like the number of keypoints and descriptors that the algorithms extract, algorithm execution time, and the quality of keypoints and descriptors extracted are considered as the performance metrics. Same data stacks were used for obtaining comparison results. In addition to comparisons for a group of well-known augmented reality applications, the best performing algorithms for varying applications were also suggested. C++ language and OpenCV library were used for the implementation of the augmented reality algorithms compared.

Keywords

Augmented Reality,Image Processing, Key Point,Descriptor

References

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Details

Primary Language

Turkish

Subjects

-

Journal Section

Research Article

Authors

Umut Tosun ^*
0000-0002-9900-7987
Türkiye

Publication Date

December 31, 2019

Submission Date

October 25, 2019

Acceptance Date

November 21, 2019

Published in Issue

Year 2019 Volume: 40 Number: 4

DOI

https://doi.org/10.17776/csj.638297

IZ

https://izlik.org/JA45ZS96EU

Cite

RIS / Bibtex

APA

Tosun, U. (2019). Comparative Analysis of the Feature Extraction Performance of Augmented Reality Algorithms. Cumhuriyet Science Journal, 40(4), 958-966. https://doi.org/10.17776/csj.638297

Öz

Comparative Analysis of the Feature Extraction Performance of Augmented Reality Algorithms

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite