Title :
Fast obstacle detection for urban traffic situations
Author :
Franke, U. ; Heinrich, S.
Author_Institution :
DaimlerChrylser AG, Stuttgart, Germany
fDate :
9/1/2002 12:00:00 AM
Abstract :
The early recognition of potentially harmful traffic situations is an important goal of vision-based driver assistance systems. Pedestrians, in particular children, are highly endangered in inner city traffic. Within the DaimlerChrysler urban traffic assistance (UTA) project, we are using stereo vision and motion analysis in order to manage those situations. The flow/depth constraint combines both methods in an elegant way and leads to a robust and powerful detection scheme. A ball bouncing on the road often implies a child crossing the street. Since balls appear very small in the images of our cameras and can move considerably fast, a special algorithm has been developed to achieve maximum recognition reliability.
Keywords :
image classification; image motion analysis; image sequences; object detection; stereo image processing; traffic engineering computing; DaimlerChrysler urban traffic assistance project; children; fast obstacle detection; flow/depth constraint; motion analysis; obstacle detection; pedestrians; potentially harmful traffic situations; stereo vision; urban traffic situations; vision-based driver assistance systems; Cities and towns; Image motion analysis; Motion analysis; Motion detection; Motion estimation; Object detection; Road accidents; Robustness; Stereo vision; Vehicles;
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
DOI :
10.1109/TITS.2002.802934