Abstract

Understanding road scenes is important in computer vision with different applications to improve road safety (e.g., advanced driver assistance systems) and to develop autonomous driving systems (e.g., Google driver-less vehicle). Current vision---based approaches rely on the robust combination of different technologies including color and texture recognition, object detection, scene context understanding. However, the performance of these approaches drops---off in complex acquisition conditions with reduced visibility (e.g., dusk, dawn, night) or adverse weather conditions (e.g., rainy, snowy, foggy). In these adverse situations any prior information about the scene is relevant to constraint the process. Therefore, in this demo we show a novel approach to obtain on---line prior information about the road ahead a moving vehicle to improve road scene understanding algorithms. This combination exploits the robustness of digital databases and the adaptation of algorithms based on visual information acquired in real time. Experimental results in challenging road scenarios show the applicability of the algorithm to improve vision---based road scene understanding algorithms. Furthermore, the algorithm can also be applied to correct imprecise road information in the database.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1007/978-3-642-33885-4_70 under the license http://www.springer.com/tdm
https://core.ac.uk/display/85815995,
https://dblp.uni-trier.de/db/conf/eccv/eccv2012w3.html#AlvarezLLG12,
https://dl.acm.org/citation.cfm?id=2404887,
https://dare.uva.nl/record/1/379998,
https://ivi.fnwi.uva.nl/isis/publications/bibtexbrowser.php?key=AlvarezECCVW2012&bib=all.bib,
https://rd.springer.com/chapter/10.1007/978-3-642-33885-4_70,
https://academic.microsoft.com/#/detail/2171679282
  • [ ]
Back to Top

Document information

Published on 31/12/11
Accepted on 31/12/11
Submitted on 31/12/11

Volume 2012, 2012
DOI: 10.1007/978-3-642-33885-4_70
Licence: Other

Document Score

0

Views 0
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?