Direct obstacle detection and motion from spatio-temporal derivatives
Autonomous vehicles need a means of detecting obstructions on its path, to avoid collision. In this paper, a novel approach to obstacle detection is presented. A camera moves on a visible ground plane with the optical axis parallel to the ground. Camera motion parameters are linearly related to first order spatio-temporal derivatives of the taken image sequence; image flow is not needed. Motion is robustly estimated using RANSAC. An error measure for each image point corresponds to the likelihood of an obstacle in that point.
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