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A practical method for ego vehicle motion estimation from video

This paper presents an original and practical method for estimating the rotation and the translation of a vehicle using video data. Imposing a movement constraint on the rotation matrix, we obtain a powerful method for estimating the rotation of the vehicle from frame to frame. Our algorithm takes as input a monocular video sequence on which originally combines procedures for feature detection and filtering, optical flow, epipolar geometry and estimation of the rotation from the obtained essential matrix. Furthermore, the obtained rotation and stereo data are used for computing the translation of the vehicle. Experiments have been performed using various urban traffic scenes which contain both curves and straight line roads.