A statistical image model for motion estimation
- 1 January 1993
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 5 (15206149) , 193-196 vol.5
- https://doi.org/10.1109/icassp.1993.319780
Abstract
Model-based object-oriented motion estimation from image sequences is addressed. A generic label field segments the scene into several continuously moving 2-D objects. An image model assuming segmentwise stationarity of the displaced frame difference (dfd) and of the estimated fields is proposed. The dfd is shown to obey a white generalized Gaussian distribution better than the commonly assumed overall white Gaussian distribution. A coupled weak smoothness constraint bounds the segments of the label field to smooth shape and the vector field to smoothness within each of those segments. A MAP (maximum a posteriori) estimator with respect to the image model is derived. Its performance is demonstrated by experimental results.Keywords
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