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A Comparison of Feature Detectors and Descriptors in RGB-D SLAM Methods

  • Oguzhan GucluEmail author
  • Ahmet Burak Can
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9164)

Abstract

In RGB-D based SLAM methods, robot motion is generally computed by detecting and matching feature points in image frames obtained from an RGB-D sensor. Thus, feature detectors and descriptors used in a SLAM method significantly affect the performance. In this work, impacts of feature detectors and descriptors on the performance of an RGB-D based SLAM method are studied. SIFT, SURF, BRISK, ORB, FAST, GFTT, STAR feature detectors and SIFT, SURF, BRISK, ORB, BRIEF, FREAK feature descriptors are evaluated in terms of accuracy and speed.

Keywords

SLAM Feature detector Feature descriptor 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer EngineeringHacettepe UniversityAnkaraTurkey

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