A Stereo Confidence Metric Using Single View Imagery
作者： Geoffrey Egnal , Max Mintz , Richard P. Wildes
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摘要: Although stereo vision research has progressed remarkably, systems still need a fast, accurate way to estimate confidence in their output. In the current paper, we explore using performance on two different images from single view as measure for binocular system incorporating that view. it seems counterintuitive search correspondence same view, such gives us precise quantitative data. Correspondences significantly far location are erroneous because there is little no motion between images. Using hand-generated ground truth, quantitatively compare this new metric with five commonly used metrics. We characteristics of each under variety conditions.
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