Title
Real-time disparity contrast combination for onboard estimation of the visibility distance
Abstract
An atmospheric visibility measurement system capable of quantifying the most common operating range of onboard exteroceptive sensors is a key parameter in the creation of driving assistance systems. This information is then utilized to adapt sensor operations and processing or to alert the driver that his onboard assistance system is momentarily inoperative. Moreover, a system capable of either detecting the presence of fog or estimating visibility distances constitutes in itself a driving assistance. In this paper, the authors present a technique to estimate the mobilized visibility distance through a use of onboard charge-coupled device cameras. The latter represents the distance to the most distant object on the road surface having a contrast above 5%. This definition is very close to the definition of the meteorological visibility distance proposed by the International Commission on Illumination. The method combines the computations of local contrasts above 5% and of a depth map of the vehicle environment using stereovision within 60 ms on a current-day computer. In this paper, both methods are described separately. Then, their combination is detailed. The method is operative night and day in every kind of meteorological condition and is evaluated; thanks to video sequences under sunny weather and foggy weather.
Year
DOI
Venue
2006
10.1109/TITS.2006.874682
IEEE Transactions on Intelligent Transportation Systems
Keywords
Field
DocType
CCD image sensors,driver information systems,stereo image processing,visibility,atmospheric visibility measurement system,driving assistance systems,onboard charge-coupled device cameras,onboard estimation,onboard exteroceptive sensors,real-time disparity contrast combination,stereovision,visibility distance,Charge coupled devices camera,contrast impairment,driving assistance,fog,meteorological visibility,stereovision
Computer vision,Visibility,User assistance,Simulation,Stereopsis,Image processing,Lidar,Artificial intelligence,Depth map,Engineering,Intelligent transportation system,Luminance
Journal
Volume
Issue
ISSN
7
2
1524-9050
Citations 
PageRank 
References 
23
2.49
16
Authors
3
Name
Order
Citations
PageRank
Hautiere, N.1273.12
Labayrade, R.2232.49
Didier Aubert336135.97