Monocular Motion Detection Using Spatial Constraints in a Unified Manner

The knowledge about moving objects plays an important role in robot navigation and driver assistance systems. Several motion detection techniques based on the optical flow were developed in the past. To our knowledge none of them exploit the available constraint envelope of a 3D point. In this paper a two-view algorithm is proposed taking advantage of the epipolar, the positive depth, and the positive height constraint, allowing the detection of independent motion and most collinear motions. The constraints are combined in a unified manner resulting in a scalar error function. This enables a direct weighting of the error with the certainty of the measured optical flow. Furthermore, the detection limit of objects moving collinear with the camera and with identical speed is investigated. Experimental results in traffic and indoor scenarios demonstrate the effectiveness of the proposed algorithm

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