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Dynamic Stereo with Self-Calibration
December 1992 (vol. 14 no. 12)
pp. 1184-1189

An approach for incremental refinement of disparity maps obtained from a dynamic stereo sequence of a static scene is presented. The approach has been implemented using a binocular stereo vision system mounted on a mobile robot. A robust least median of squares based algorithm is given for recovering the camera motion between successive viewpoints, which provides a self-calibration mechanism. The recovered motion is utilized for recursive disparity prediction and refinement using a robust Kalman filter model.

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Index Terms:
disparity map refinement; camera motion recovery; self-calibration; incremental refinement; dynamic stereo sequence; binocular stereo vision system; mobile robot; robust least median of squares based algorithm; recursive disparity prediction; robust Kalman filter; calibration; filtering and prediction theory; image sequences; Kalman filters; least squares approximations; mobile robots; motion estimation; stereo image processing
Citation:
A.P. Tirumalai, B.G. Schunck, R.C. Jain, "Dynamic Stereo with Self-Calibration," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 12, pp. 1184-1189, Dec. 1992, doi:10.1109/34.177383
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