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Fast randomized multi-scale energy minimization for inferring depth from stereo image pairs
Fast randomized multi-scale energy minimization for inferring depth from stereo image pairs
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机译:快速随机化多尺度能量最小化以从立体图像对推断深度
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摘要
An image processing module infers depth from a stereo image pair according to a multi-scale energy minimization process. A stereo image pair is progressively downsampled to generate a pyramid of downsampled image pairs of varying resolution. Starting with the coarsest downsampled image pair, a disparity map is generated that reflects displacement between corresponding pixels in the stereo image pair. The disparity map is then progressively upsampled. At each upsampling stage, the disparity labels are refined according to an energy function. The disparity labels provide depth information related to surfaces depicted in the stereo image pair.
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