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Chapter

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Title

Leveraging Object Recognition in Reliable Vehicle Localization from Monocular Images

Authors

[ 1 ] Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ SzD ] doctoral school student | [ P ] employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics and electrical engineering

Year of publication

2020

Chapter type

chapter in monograph / paper

Publication language

english

Abstract

EN We present the processing pipeline of a monocular vision system that successfully performs the task of detecting, identifying and localizing a city bus electric charger station. This task is essential to the operation of an advanced driver assistance system that helps the driver to dock the long vehicle at the charging station. The focus is on the role of machine learning techniques in developing a robust detection and classification procedure that allows our system to localize the camera with respect to the charger even from long distances. We demonstrate that the learned detection procedure improves robustness of the vision techniques for monocular localization, while the geometric relations estimated by our system can be used to improve the learning results.

Date of online publication

28.02.2020

Pages (from - to)

195 - 204

DOI

10.1007/978-3-030-40971-5_18

URL

https://link.springer.com/chapter/10.1007/978-3-030-40971-5_18

Book

Automation 2020: Towards Industry of the Future : Proceedings of Automation 2020, March 18–20, 2020, Warsaw, Poland

Presented on

Automation 2020, 18-20.03.2020, Warsaw, Poland

License type

other

Ministry points / chapter

20

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