Still corresponding points extraction using a moving monocular camera with a motion sensor

Toshihiro Akamatsu, Fangyan Dong, Kaoru Hirota

Research output: Contribution to journalArticlepeer-review

Abstract

The method of extracting still corresponding points proposed in this paper uses a moving monocular camera connected to a 6-axis motion sensor. It classifies corresponding points between two consecutive frames containing still/moving objects and chooses corresponding points appropriate for 3D measurement. Experiments are done extracting still corresponding points with 2 scenes from original computer graphics images. Results for scene 1 show that accuracy is 0.98, precision 0.96, and recall 1.00. Robustness against sensor noise is confirmed. Extraction experiment results with real scenes show that accuracy is 0.86, precision 0.88, and recall 0.94. We plan to include the proposed method in 3D measurement with real images containing still/moving objects and to apply it to obstacles avoidance for vehicles and to mobile robot vision systems.

Original languageEnglish
Pages (from-to)319-329
Number of pages11
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume19
Issue number2
DOIs
Publication statusPublished - 1 Mar 2015
Externally publishedYes

Keywords

  • 3D measurement
  • 6-Axis motion sensor
  • Corresponding points classification
  • Moving monocular camera

Fingerprint

Dive into the research topics of 'Still corresponding points extraction using a moving monocular camera with a motion sensor'. Together they form a unique fingerprint.

Cite this