Realtime detection and localization of a road from an aerial image is an emerging research area that can be applied to vision-based navigation of unmanned air vehicles. Existing realtime and non-realtime road detection algorithms focus on pre-defined road types, and a single algorithm cannot handle a large variety of road types such as dirt roads, local streets, and freeways. An algorithm to detecting any types of corridors is presented. First, a corridor structure is automatically learned at runtime with a single example. The corridor structure is represented as a cross-sectional 1-D signal segment. The learning procedure is to find the maximum correlation of such signals. The realtime detection consists of 1-D signal matching and robust fitting on the matching result. Realtime detection results on various road images are presented.
Realtime Road Detection by Learning from One Example
01.01.2005
918261 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Realtime lane tracking of curved local road
IEEE | 2006
|Realtime Image Processing Algorithms for the Detection of Road and Environmental Conditions
British Library Conference Proceedings | 2005
|ROAD TRAFFIC PREDICTION SYSTEM BASED ON REALTIME ROAD VELOCITY DATA AND THEREOF METHOD
Europäisches Patentamt | 2025