Finding wheels of vehicles in stereo images

In model-based recognition of vehicles, wheels can play a key role. Certainly, they are the most prominent features of a vehicle. However, finding wheels in an image is a difficult task. Generally, a wheel appears as an ellipse in an image. An obvious way of finding ellipses is to use the Hough transform. The difficulty is that the search space is 5-dimensional. This curse of dimensionality is with us no matter what method we use to search for the ellipses. We use a stereo pair of images to reduce the search space. The idea is to determine from the stereo images the 3-D orientation of the plane containing the wheels, and then apply an appropriate transformation on either of the two stereo images such that in the new image the wheels will be circular. The search space is then only 3-dimensional. In this paper we describe this approach in detail and show some experimental results.