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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References
Li L., Duncan, J. H.: 3D translational motion and structure from binocular image flows. IEEE PAMI, 15 (1993) 657–667
Hu, X., Ahuja, N.: Motion and structure estimation using long sequence motion models. Image and Vision Computing, 11 (1993) 549–569
Matthies, L., Szeliski, R., Kanade, T.: Kalman filter-based algorithms for estimating depth from image sequences. IJCV, 3 (1989) 209–238
Cui, N. et al.: Recursive-batch estimation of motion and structure from monocular image sequences. CVGIP: Image Understanding, 59 (1994) 154–170
Yang, J. A.: Computing general 3Dmotion of objects without correspondence from binocular image flow, Journal of Computer, 18 (1995) 849–857
Yang, J. A.: A neural paradigm of time-varying motion segmentation. Journal of Computer Science and Technology, 9 (1999) 238–251
Zhang, Z., Faugeras O. D.: Three-dimensional motion computation and object segmentation in a long sequence of stereo frames. IJCV, 7 (1992) 211–242
De Micheli, E. et al.: The accuracy of the computation of optical flow and the recovery of motion parameters. IEEE PAMI, 15 (1993) 434–447
Heeger, D. J., Jepson, A. D.: Subspace methods for recovering rigid motion 1: algorithm and implementation. IJCV, 7 (1992) 95–117
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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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