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  4. Evaluation of binary keypoint descriptors
 
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2013
Conference Paper
Title

Evaluation of binary keypoint descriptors

Abstract
In this paper an evaluation of state-of-the-art binary keypoint descriptors, namely BRIEF, ORB, BRISK and FREAK, is presented. In contrast to previous evaluations we used the Stanford Mobile Visual Search (SMVS) data set because binary descriptors are mainly used in mobile applications. This large data set does provide a lot of characteristic transformations for mobile devices, but no ground truth data. The often used Oxford data set is used only for validation purposes. We use ratio-test and RANSAC (RANdom SAmple Consensus) for evaluation and present results for accuracy, precision and average number of best matches as performance metrics. The validity of the results is also checked by evaluating these binary keypoint descriptors on Oxford data set. The obtained results show that BRISK is the keypoint descriptor which gives highest percentage of precision and largest number of best matches among all the binary descriptors. Next to BRISK is FREAK, which offers comparably good result.
Author(s)
Bekele, D.
Teutsch, Michael
Schuchert, Tobias
Mainwork
20th IEEE International Conference on Image Processing, ICIP 2013. Proceedings  
Conference
International Conference on Image Processing (ICIP) 2013  
Open Access
File(s)
Download (668.73 KB)
Rights
Use according to copyright law
DOI
10.1109/ICIP.2013.6738753
10.24406/publica-r-382254
Additional link
Full text
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Keyword(s)
  • binary descriptors

  • matching

  • recognition

  • invariance

  • evaluation

  • mobile feature tracking

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