Segmenting Traffic Scenes from Grey Level and Motion Information
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This paper is concerned with an efficient estimation and segmentation of 2D motion from image sequences, with the focus on traffic monitoring applications. In order to reduce the computational load to achieve real-time implementation, the proposed approach makes use of simplifying assumptions that the camera is stationary, and that the projection of vehicles motion on the image plane can be approximated by translation. We show that satisfactory results can be achieved even under such apparently restrictive assumptions. The use of 2D motion analysis and the pre-segmentation stage significantly reduces the computational load, and the region-based motion estimator gives robustness to noise and changes in the illumination conditions.
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