Abstract
This paper presents how to estimate the left and right monocular motion and structure parameters of two stereo image sequences including direction of translation, relative depth, observer rotation and rotational acceleration, and how to compute absolute depth, absolute translation and absolute translational acceleration parameters at each frame. For improving the accuracy of the computed parameters and robustness of the algorithm, A Kalman filter is used to integrate the parameters over time to provide a “best” estimation of absolute translation at each time.
This work was supported by The National Natural Science Foundation of China under contracts No. 69585002 and No. 69785003
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© 2000 Springer-Verlag Berlin Heidelberg
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Yang, J.A., Yang, X.M. (2000). Robust, Real-Time Motion Estimation from Long Image Sequences Using Kalman Filtering. In: Lee, SW., Bülthoff, H.H., Poggio, T. (eds) Biologically Motivated Computer Vision. BMCV 2000. Lecture Notes in Computer Science, vol 1811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45482-9_61
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DOI: https://doi.org/10.1007/3-540-45482-9_61
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