1. Efficient Stop Sign Detection Using 3D Scene Geometry Jeffrey Schlosser CS 223b March 17, 2008

2. Problem Statement and Data  Quickly and reliably detect stop signs using data acquired from a camera mounted on an autonomous vehicle

3. Approach  Haar classifiers used to form representation of stop signs  Utilize known geometry:

4. Approach (cont.) Possible locations and scales of stop signs

5. Results: Single Image Processing time: 1117 milliseconds Processing time: 275 milliseconds Traditional Algorithm (comprehensive search) Intelligent Algorithm (using 3D scene context)

6. Results: Image Sequence  Average Processing time: 253 milliseconds  3.9 fps  1.53 FP/image  Average Processing time: 71 milliseconds  14 fps  0.73 FP/image Intelligent Algorithm (using 3D scene context) Traditional Algorithm (comprehensive search)  Even faster times possible with better information

7. Questions?