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The shift value is then assigned as a disparity value.
A disparity value is obtained for each candidate pixel.
The estimated disparity value of the unknown pixel can be obtained by minimizing the energy function.
The average disparity value error of pixels that have been classified as bad pixels. .
It allows computing a confidence measure for attributing a disparity value to the pixel.
The average disparity value error of pixels that have been classified as bad pixels.
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For the potential candidate pixels, we compute the standard deviation of the disparity values.
The false matches corresponding to wrong disparity values are detected automatically using the confidence-measure technique.
Full resolution images have up to 3000 × 2000 pixels and no more than 800 disparity values. .
Unlike intensities, disparity values are generally stable over time regardless of changes in lighting.
We finally interpolate the disparity values of the overlapping frames in consecutive batches for smoother transitions.
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