Robust ground surface map generation using vehicle-mounted stereo camera

We propose a robust method for incrementally estimating a regular-grid ground surface map from stereo image sequences captured by nearly front-looking vehicle-mounted stereo cameras. The method simultaneously estimates a camera ego-motion and vertex heights of a regular mesh, which is composed of piecewise triangular patches drawn on a level plane in the ground coordinate system, by minimizing pixel value differences over the ground surface. The method combinationally uses feature-based approach and pixel-based approach for robustly estimating ego-motion parameters. We also show that this combination is beneficial for removing outlier pixels, which mainly represent the edge of the self-shadow area on the ground surface. The validity of the proposed method is demonstrated through experiments using real images.