| Y. Weiss. Bayesian motion estimation and segmentation. PhD thesis, M.I.T., 1998. |
....which will be a function of location, will specify which recipe has to be used within each region and, therefore, will provide a segmentation of the image. To estimate the parameters of the mixture (shape recipes and weights) given known shape and the associated image, we use the EM algorithm [15]. We encourage continuity for the weights Pn as neighboring pixels are likely to belong to the same material. We use the mean field approximation to implement the spatial smoothness prior in the E step, suggested in [ 15] Figure 6 shows a segmentation example. a) is a fractal shape, with ....
....weights) given known shape and the associated image, we use the EM algorithm [15] We encourage continuity for the weights Pn as neighboring pixels are likely to belong to the same material. We use the mean field approximation to implement the spatial smoothness prior in the E step, suggested in [ 15]. Figure 6 shows a segmentation example. a) is a fractal shape, with diagonal left structure across the top half, and diagonal right structure across the bottom half. Onto that shape, we painted two different Phong shading renderings in the two vertical halves, shown in (b) the right half is ....
Y. Weiss. Bayesian motion estimation and segmentation. PhD thesis, M.I.T., 1998. http://www.cs.huji.ac.il/yweiss/thesis.html.
....perceptual behavior [11] 18] 25] 28] usually using psychophysical stimuli, e.g. plaids and random dot images, and have not been tested using real motion scenes. Unlike neural network methods, image processing algorithms can deal with real scenes [3] 5] 7] 8] 16] 26] 29] 33] [34]. However, they also fail to consider all of the three challenges simultaneously. One class of algorithms employs motion energy filters for motion detection [2] 21] 26] 33] These algorithms can represent motion transparency. However, they are fundamentally limited to translational motion ....
Y. Weiss, "Bayesian motion estimation and segmentation," Ph.D. dissertation, Dept. Brain Cognitive Sci., Mass. Inst. Technol., Cambridge, 1998.
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Y. Weiss. Bayesian motion estimation and segmentation. PhD thesis, M.I.T., 1998.
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Y. Weiss, Bayesian motion estimation and segmentation. PhD thesis, MIT, May 1998.
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