By Topic

Real-time vehicle and lane detection with embedded hardware

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Kaszubiak, J. ; Inst. for Electron., Signal Process. & Commun., Magdeburg Univ., Germany ; Tornow, M. ; Kuhn, R.W. ; Michaelis, B.
more authors

For autonomously acting robots and driver assistance systems powerful optical stereo sensor systems are required. Object positions and environmental conditions have to be acquired in real-time. In this paper an algorithm based on a hardware-software co-design is applied. A depth-map is generated with a hierarchical detection method. A depth-histogram is generated by using the density distribution of the disparity in the depth-map. It is used for object detection. The object clustering can be accomplished without calculation of 3D-points, due to the almost identical mapping of the objects over the whole distance, within the histogram. A lane detection is applied by using a Hough transform. The suitability at night and the detection of small objects like bikers is proven.

Published in:

Intelligent Vehicles Symposium, 2005. Proceedings. IEEE

Date of Conference:

6-8 June 2005