Workshop at the European Conference on Computer Vision

ECCV 2014: Computer Vision - ECCV 2014 Workshops pp 194-208

Augmenting Vehicle Localization Accuracy with Cameras and 3D Road Infrastructure Database

  • Lijun Wei
  • Bahman Soheilian
  • Valérie Gouet-Brunet
Conference paper

DOI: 10.1007/978-3-319-16178-5_13

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8925)
Cite this paper as:
Wei L., Soheilian B., Gouet-Brunet V. (2015) Augmenting Vehicle Localization Accuracy with Cameras and 3D Road Infrastructure Database. In: Agapito L., Bronstein M., Rother C. (eds) Computer Vision - ECCV 2014 Workshops. ECCV 2014. Lecture Notes in Computer Science, vol 8925. Springer, Cham

Abstract

Accurate and continuous vehicle localization in urban environments has been an important research problem in recent years. In this paper, we propose a landmark based localization method using road signs and road markings. The principle is to associate the online detections from onboard cameras with the landmarks in a pre-generated road infrastructure database, then to adjust the raw vehicle pose predicted by the inertial sensors. This method was evaluated with data sequences acquired in urban streets. The results prove the contribution of road signs and road markings for reducing the trajectory drift as absolute control points.

Keywords

Vehicle localization Road infrastructure database Road signs Road markings 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lijun Wei
    • 1
  • Bahman Soheilian
    • 1
  • Valérie Gouet-Brunet
    • 1
  1. 1.IGN, SRIG, MATISUniversité Paris-EstSaint MandéFrance

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