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Type: Conference paper
Title: RRD-SLAM: Radial-distorted rolling-shutter direct SLAM
Author: Kim, J.
Latif, Y.
Reid, I.
Citation: IEEE International Conference on Robotics and Automation, 2017, pp.5148-5154
Publisher: IEEE
Issue Date: 2017
Series/Report no.: IEEE International Conference on Robotics and Automation (ICRA)
ISBN: 9781509046331
ISSN: 1050-4729
Conference Name: IEEE International Conference on Robotics and Automation (ICRA) (29 May 2017 - 3 Jun 2017 : Singapore)
Statement of
Jae-Hak Kim, Yasir Latif and Ian Reid
Abstract: In this paper, we present a monocular direct semi-dense SLAM (Simultaneous Localization And Mapping) method that can handle both radial distortion and rolling-shutter distortion. Such distortions are common in, but not restricted to, situations when an inexpensive wide-angle lens and a CMOS sensor are used, and leads to significant inaccuracy in the map and trajectory estimates if not modeled correctly. The apparent naive solution of simply undistorting the images using pre-calibrated parameters does not apply to this case since rows in the undistorted image are no longer captured at the same time. To address this we develop an algorithm that incorporates radial distortion into an existing state-of-the-art direct semi-dense SLAM system that takes rolling-shutters into account. We propose a method for finding the generalized epipolar curve for each rolling-shutter radially distorted image. Our experiments demonstrate the efficacy of our approach and compare it favorably with the state-of-the-art in direct semi-dense rolling-shutter SLAM.
Rights: Copyright © 2017 IEEE
DOI: 10.1109/ICRA.2017.7989602
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Appears in Collections:Aurora harvest 3
Australian Institute for Machine Learning publications
Computer Science publications

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