1. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Estimation of the Visibility Distance by Stereovision: a Generic Approach Nicolas Hautière, Raphaël Labayrade, Didier Aubert LIVIC (LCPC-INRETS) Vehicle-Infrastructure-Driver Interactions Unit Versailles - France

2. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Measurement of Visibility Distance Our work is based on a definition of the International Commission on Illumination [1]Our work is based on a definition of the International Commission on Illumination [1] « The meteorological visibility is the greatest distance at which a black object of suitable dimensions can be recognized by day against the horizon sky. » [1] CIE, 1987. International Lighting Vocabulary, CIE Publ. No. 17.4.

3. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Previous work We developed a Koschmieder’s Law based method [2]:We developed a Koschmieder’s Law based method [2]: detecting daylight fog,detecting daylight fog, estimating the meteorological visibility.estimating the meteorological visibility. Extraction of a target region Composition of a measurement bandwidth Measurement and derivative of the luminance curve Extraction of an inflection point V met = 50m Instanciation of Koschmieder’s Law Estimation the meteorological visibility [2] N. Hautière, D. Aubert.. 10 th ITS World, Madrid, 2003. [2] N. Hautière, D. Aubert. Driving assistance : Automatic fog detection and measure of the visibility distance. 10 th ITS World, Madrid, 2003.

4. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Discussion The method needs only one camera, and the presence of the road and the sky in the image to run properly.The method needs only one camera, and the presence of the road and the sky in the image to run properly. The method is restricted to daylight fog situations.The method is restricted to daylight fog situations. => Development of a new generic approach including a new visibility distance: Measurement of the distance to the most distant object in the scene having a contrast above 5 %. + -

5. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 New Visibility Distance d V mob (a) V max V mob mobilized visibility distance, The distance to the most distant object in the scene having a contrast above 5 %. V max mobilizable visiblity distance, V max mobilizable visiblity distance, V met meteorological visibility distance. V met meteorological visibility distance. The greatest distance at which a black object of suitable dimensions can be recognized by day against the horizon sky. With a contrast theshold of 5 %, we found the following relationship: V mob  V max  V met d V mob V max (b)

6. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Generic approach 1.Computation of a depth map of the vehicle environment, 2.Extraction of picture elements having a contrast above 5 %, 3.Estimation of the mobilized visibility distance.

7. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Depth computation by stereovision [3] Grabbing the left and right images Computing a disparity map Computing the “v-disparity” representation Extracting global surfaces Improving the disparity map and extracting the obstacle areas [3] R. Labayrade, D. Aubert. In-Vehicle Obstacles Detection and Characterization by Stereovision. IEEE ICVS, Graz, Austria, 2003.

8. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Depth computation by stereovision Results

9. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Construction of the border associated with s: F(s)={(x,x 1 ) / x  V 4 (x 1 ) and Min(f(x),f(x 1 ))  s<Max(f(x),f(x 1 )) Computation of the mean contrast associated with s: Computation of C>5% Principle of Köhler’s binarization technique [4] f(x 1 ) f(x) C x,x1 (s) s x x1x1 F(s) [4] R. Köhler. A segmentation technique based on tresholding. CVGIP, 15:319-338, 1981  s  [0,255] We find s 0 so as: Finally, the evaluated contrast on F(s) is 2C(s 0 ). where

10. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Computation of C>5% Adaptation to the logarithmic contrast used by CIEAdaptation to the logarithmic contrast used by CIE Algorithmic optimizationsAlgorithmic optimizations MIN-MAX images precomputations,MIN-MAX images precomputations, Sliding vicinities,Sliding vicinities, Parallelization…Parallelization… Before: 14 s on a full image 360x288Before: 14 s on a full image 360x288 Now: 350 msNow: 350 ms Good properties: robustness to noise, precision of edges detection Good properties: robustness to noise, precision of edges detection

11. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Computation of C>5% Results

12. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Estimation of the mobilized visibility distance. Horizon line Computation time on a 2.4 GHz PC Image 360x288 60 ms

13. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Experimental results Sunny weather

14. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Experimental results Foggy weather

15. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Experimental results Night foggy weather

16. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Conclusion We have presented a generic method:We have presented a generic method: estimating the mobilized visibility distance, estimating the mobilized visibility distance, based on the stereovision« v-disparity » approach, based on the stereovision« v-disparity » approach, computing the local contrast above 5 %, computing the local contrast above 5 %, performed within 60 ms on a current-day PC, performed within 60 ms on a current-day PC, reliable in lots of meteorological and illumination conditions. reliable in lots of meteorological and illumination conditions.

17. May 16-18, 2005 - Tsukuba Science City, Japan Machine Vision Applications 2005 Thank you for your attention !