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A novel monocular visual odometer method based on Kinect and improved SURF algorithm

  • Li Jun Zhang
  • , Fei Chen
  • China University of Geosciences, Wuhan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The paper proposes a novel monocular visual odometer method based on Kinect sensor made by Microsoft and the improved SURF algorithm. Firstly the Kinect sensor capture color images and depth images of the surrounding environment, then we use the improved SURF algorithm to extract feature points of the color images and match for them. At last, map what we get with the depth image and estimate the path information of the robot by doing 3D reconstruction and using the the least square mean value theorem. Experimental results show that by using this new method, the average matching accuracy reaches 92.6%. And even in a dynamic environment, it shows good robustness, so it comes down to the conclusion that the combination of the Kinect sensor and the improved SURF algorithm applied to visual odometer is a simple and effective method.

Original languageEnglish
Title of host publicationMechatronics Engineering, Computing and Information Technology
PublisherTrans Tech Publications
Pages4081-4084
Number of pages4
ISBN (Print)9783038351153
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event2014 International Conference on Mechatronics Engineering and Computing Technology, ICMECT 2014 - Shanghai, China
Duration: 9 Apr 201410 Apr 2014

Publication series

NameApplied Mechanics and Materials
Volume556-562
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2014 International Conference on Mechatronics Engineering and Computing Technology, ICMECT 2014
Country/TerritoryChina
CityShanghai
Period9/04/1410/04/14

Keywords

  • Improved SURF
  • Kinect
  • Least square mean value theorem
  • Visual odometer

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