Abstract
The trajectory of a moving object can be used to understand the motion pattern and predict future motion. In this chapter, we investigate the issues related to motion modeling, understanding and prediction. Based on dynamics, a locally constant angular momentum (LCAM) model is introduced. The model is local in the sense that it is applied to a limited number of image frames at a time. Specifically, the model constrains the motion, over a local frame subsequence, to be a superposition of precession and translation. Thus, the instantaneous rotation axis of the object is allowed to change with time. The trajectory of the rotation center is approximated by a vector polynomial. The parameters of the model evolve in time so that they can adapt to long term changes in motion characteristics. Based on the assumption that the motion is smooth, object positions and motion in the near future can be predicted, and short missing subsequences can be recovered.
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© 1993 Springer-Verlag Berlin Heidelberg
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Weng, J., Huang, T.S., Ahuja, N. (1993). Motion Modeling and Prediction. In: Motion and Structure from Image Sequences. Springer Series in Information Sciences, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77643-4_8
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DOI: https://doi.org/10.1007/978-3-642-77643-4_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-77645-8
Online ISBN: 978-3-642-77643-4
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