Measuring uncertainty in human visual segmentation
Fig 7
Variability in human segmentation reflects image uncertainty.
From left to right: tested images, segmentation maps, probabilistic maps of the left region and entropy maps corresponding to the reconstructed probabilistic maps i.e. pi[1] log (pi[1]) + pi[2] log (pi[2]) (average entropy ± 3 standard errors is indicated by the text in white). Top: low uncertainty case (texture orientation distributions are weakly overlapping). Bottom: high uncertainty case (texture orientation distributions are strongly overlapping). In all panels, the red line represents the ground truth boundary between the two segments (shown only for visualization purposes, not in the real experiments). Maps are reconstructed without regularization (λ = 0).