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Depth Estimation from Motion Parallax: Experimental Evaluation

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

Details

Original languageEnglish
Title of host publication2019 26th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS)
PublisherIEEE
ISBN (Electronic)978-5-91995-065-3
DOIs
Publication statusPublished - 30 May 2019
Publication typeA4 Article in a conference publication
EventSAINT PETERSBURG INTERNATIONAL CONFERENCE ON INTEGRATED NAVIGATION SYSTEMS -
Duration: 1 Jan 1900 → …

Conference

ConferenceSAINT PETERSBURG INTERNATIONAL CONFERENCE ON INTEGRATED NAVIGATION SYSTEMS
Period1/01/00 → …

Abstract

We propose a method to estimate the distance to objects based on the complementary nature of monocular image sequences and camera kinematic parameters. The fusion of camera measurements with the kinematics parameters that are measured by an IMU and an odometer is performed using an extended Kalman filter. Results of field experiments with a wheeled robot corroborated the results of the simulation study in terms of accuracy of depth estimation. The performance of the approach in depth estimation is strongly affected by the mutual observer and feature point geometry, measurement accuracy of the observer’s motion parameters and distance covered by the observer. It was found that under favorable conditions the error in distance estimation does not exceed 1% of the distance to a feature point. This approach can be used to estimate distance to objects located hundreds of meters away from the camera.

Publication forum classification

Field of science, Statistics Finland