Journal of Real-Time Image Processing

, Volume 16, Issue 2, pp 289–304 | Cite as

Park marking-based vehicle self-localization with a fisheye topview system

  • Sebastian HoubenEmail author
  • Marcel Neuhausen
  • Matthias Michael
  • Robert Kesten
  • Florian Mickler
  • Florian Schuller
Original Research Paper


Accurately self-localizing a vehicle is of high importance as it allows to robustify nearly all modern driver assistance functionality, e.g., lane keeping and coordinated autonomous driving maneuvers. We examine vehicle self-localization relying only on video sensors, in particular, a system of four fisheye cameras providing a view surrounding the car, a setup currently growing popular in upper-class cars. The presented work aims at an autonomous parking scenario. The method is based on park markings as orientation marks since they can be found in nearly every parking deck and require only little additional preparation. Our contribution is twofold: (1) we present a new real-time capable image processing pipeline for topview systems extracting park markings and show how to obtain a reliable and accurate ego pose and ego motion estimation given a coarse pose as starting point. (2) The aptitude of this often neglected sensor array for vehicle self-localization is demonstrated. Experimental evaluation yields a precision of 0.15 \(\pm\) 0.18 m and 2.01\(^{\circ }\; \pm\) 1.91\(^{\circ }\).


Vehicle self-localization Fisheye camera Topview Park marking detection Kalman filter 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Sebastian Houben
    • 1
    Email author
  • Marcel Neuhausen
    • 1
  • Matthias Michael
    • 1
  • Robert Kesten
    • 2
  • Florian Mickler
    • 3
  • Florian Schuller
    • 3
  1. 1.Institut für NeuroinformatikRuhr-Universität BochumBochumGermany
  2. 2.GIGATRONIK IngolstadtGaimersheimGermany
  3. 3.Audi Electronics Venture GmbHGaimersheimGermany

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