Efficient Visual Odometry Using a Structure-Driven Temporal Map

Jose Martinez-Carranza*, Andrew Calway

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

9 Citations (Scopus)


We describe a method for visual odometry using a single camera based on an EKF framework. Previous work has shown that filtering based approaches can achieve accuracy performance comparable to that of optimisation methods providing that large numbers of features are used. However, computational requirements are signicantly increased and frame rates are low. We address this by employing higher level structure - in the form of planes - to efficiently parameterise features and so reduce the filter state size and computational load. Moreover, we extend a 1-point RANSAC outlier rejection method to the case of features lying on planes. Results of experiments with both simulated and real-world data demonstrate that the method is effective, achieving comparable accuracy whilst running at significantly higher frame rates.

Original languageEnglish
Title of host publicationInternational Conference on Robotics and Automation (ICRA)
Place of PublicationNEW YORK
PublisherIEEE Computer Society
Number of pages6
ISBN (Print)978-1-4673-1405-3
Publication statusPublished - 1 May 2012
EventIEEE International Conference on Robotics and Automation (ICRA) - St Paul, Mongolia
Duration: 14 May 201218 May 2012


ConferenceIEEE International Conference on Robotics and Automation (ICRA)


  • SLAM


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