Enhanced visual odometry algorithm based on elite selection method and voting system

Hao Shen, Chen Chien Hsu, Wei-Yen Wang, Yin Tien Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we address the problems of camera pose estimation accuracy and runtime efficiency by incorporating an elite selection method and a voting system to a conventional visual odometry (VO) method, called the 'enhanced VO algorithm'. The use of elite selection method improves the efficiency of perspective-3-point (P3P) algorithm by only employing an elite subset of landmarks to estimate the camera pose. The proposed voting system, on the other hand, provides reliable consensus set derived from random sample consensus (RANSAC) algorithm such that accuracy of camera pose estimations can be increased. To verify the performances of the proposed approach, we conducted various experiments using a Kinect RGB-D sensor, and the results show that the proposed VO system performs well in terms of not only estimation accuracy but also computational time.

Original languageEnglish
Title of host publication2017 IEEE 7th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2017
PublisherIEEE Computer Society
Pages99-100
Number of pages2
ISBN (Electronic)9781509040148
DOIs
Publication statusPublished - 2017 Dec 14
Event7th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2017 - Berlin, Germany
Duration: 2017 Sep 32017 Sep 6

Publication series

NameIEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Volume2017-September
ISSN (Print)2166-6814
ISSN (Electronic)2166-6822

Other

Other7th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2017
CountryGermany
CityBerlin
Period17/9/317/9/6

Keywords

  • Kinect RGB-D sensor
  • Perspective-3-point
  • RANSAC
  • SURF
  • Visual odometry

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Media Technology

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