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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

Evaluation of Iterative Calibration of Vehicle Cameras Using Reference Information from Traffic Signs

verfasst von : Alexander Hanel, Uwe Stilla

Erschienen in: Smart Cities, Green Technologies and Intelligent Transport Systems

Verlag: Springer International Publishing

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Abstract

Intrinsic camera parameters can be estimated by camera calibration using multiple images of a priori known reference points on a test field. In particular during driving, vehicle cameras might be exposed to mechanical and thermal effects, leading to a change of these parameters over time and making iterative camera calibration useful to correct for these changes. As on roads no special test fields are available, reference information has to be extracted from road scene images. In this contribution, a method for iterative calibration of a vehicle camera using references on traffic signs is proposed. The references are obtained from the shape of traffic signs detected in road scene images, exploiting that the shape is known a priori. A test with a road scene image sequence acquired during a test drive in a car park equipped with traffic signs shows no decrease in the standard deviation of the parameters iteratively estimated with the proposed method compared to test field calibration.

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Vorheriges Kapitel Real-Time Overtaking Vehicle Detection Based on Optical Flow and Convolutional Neural Network
Nächstes Kapitel Implementation and Investigation of a Weather- and Jam Density-Tuned Network Perimeter Controller
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Metadaten
Titel
Evaluation of Iterative Calibration of Vehicle Cameras Using Reference Information from Traffic Signs
verfasst von
Alexander Hanel
Uwe Stilla
Copyright-Jahr
2019
Buch
Smart Cities, Green Technologies and Intelligent Transport Systems

Print ISBN: 978-3-030-26632-5

Electronic ISBN: 978-3-030-26633-2

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-26633-2_12