Registration Based on ORB and FREAK Features for Augmented Reality Systems

Yang Yu, Yingchun Guo, Ruili Wang, Susha Yin, Ming Yu

Research output: Journal PublicationArticlepeer-review

3 Citations (Scopus)

Abstract

This paper proposes a novel registration method for augmented reality (AR) systems based on Oriented FAST and Rotated BRIEF (ORB) and Fast Retina Keypoint (FREAK) natural features. In the proposed ORB-FREAK method, feature extraction is implemented based on the combination of ORB and FREAK, and the feature points are matched using Hamming distance. To get good matching points, cross-checks and least median squares are used to perform outlier filtration, and camera pose is estimated using the matched points. Finally, AR is rendered. Experiments show that the proposed method improves the speed of registration to be in real time; the proposed method can accurately register the target object under the circumstances of partial occlusion of the object; and it also can overcome the effects of rotation, scale change, ambient light and distance.

Original languageEnglish
Pages (from-to)192-200
Number of pages9
JournalTransactions of Tianjin University
Volume23
Issue number2
DOIs
Publication statusPublished - 1 Mar 2017
Externally publishedYes

Keywords

  • Augmented reality registration
  • Fast retina keypoint
  • Oriented FAST and rotated BRIEF
  • Pose estimation

ASJC Scopus subject areas

  • General

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