Publication detail

Robust detection of shady and highlighted roads for monocular camera based navigation of UGV

PETYOVSKÝ, P. MIKŠÍK, O. ŽALUD, L. JURA, P.

Original Title

Robust detection of shady and highlighted roads for monocular camera based navigation of UGV

Type

conference paper

Language

English

Original Abstract

This paper addresses the problem of UGV navigation in various environments and lightning conditions. Previous approaches use a combination of different sensors, or work well, only in scenarios with noticeable road marking or borders. Our robot is used for chemical, nuclear and biological contamination measurement. Thus, to avoid complications with decontamination, only a monocular camera serves as a sensor since it is already equipped. In this paper, we propose a novel approach a fusion of frequency based vanishing point estimation and probabilistically based color segmentation. Detection of a vanishing point, is based on the estimation of a texture flow, produced by a bank of Gabor wavelets and a voting function. Next, the vanishing point defines the training area, which is used for self-supervised learning of color models. Finally, road patches are selected by measuring of the roadness score. A few rules deal with dark cast shadows, overexposed highlights and adaptivity speed. In addition to the robustness of our system, it is easy-to-use since no calibration is needed.

Keywords

Adaptation models , Cameras , Estimation , Image color analysis , Roads , Robots , Training

Authors

PETYOVSKÝ, P.; MIKŠÍK, O.; ŽALUD, L.; JURA, P.

RIV year

2011

Released

10. 5. 2011

Location

Shanghai

ISBN

978-1-61284-386-5

Book

Proceedings of ICRA 2011

Edition

1

Edition number

1

Pages from

64

Pages to

71

Pages count

8

BibTex

@inproceedings{BUT76566,
  author="Petr {Petyovský} and Ondřej {Mikšík} and Luděk {Žalud} and Pavel {Jura}",
  title="Robust detection of shady and highlighted roads for monocular camera based navigation of UGV",
  booktitle="Proceedings of ICRA 2011",
  year="2011",
  series="1",
  number="1",
  pages="64--71",
  address="Shanghai",
  isbn="978-1-61284-386-5"
}