We propose an algorithm that simultaneously extracts disparities and alpha matting information given a stereo image pair. Our method divides the reference image into a set of overlapping, partially transparent color segments. Each segment pixel is assigned an alpha value and color. The disparity inside the segment is modeled via a plane. The goodness of alphas, colors and disparity planes is measured by a new energy function. Its basic idea is to use the three parameters for generating arti\ufb01cial views representing the left and right images. If alphas, colors and disparity planes are correct, these arti\ufb01cial images should be very similar to the real ones. For generating the arti\ufb01cial right view, we warp all pixels of the left into the geometry of the right image using the disparity planes. We introduce the assumption of constant solidity in order to correctly model how pixels\u2019 alpha values are affected by the warping operation. Experimental results on the Middlebury set show that our algorithm gives good results in comparison to the state-of-the-art in stereo matching.<\/p>\n","protected":false},"excerpt":{"rendered":"
We propose an algorithm that simultaneously extracts disparities and alpha matting information given a stereo image pair. Our method divides the reference image into a set of overlapping, partially transparent color segments. Each segment pixel is assigned an alpha value and color. The disparity inside the segment is modeled via a plane. The goodness of 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