Robust Image Segmentation Using Resampling and Shape Constraints
IEEE Transactions on Pattern Analysis and Machine Intelligence
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ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
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This paper presents a database containing "ground truth" segmentations produced by humans for images of a wide variety of natural scenes. We define an error measure which quantifies the consistency between segmentations of differing granularities and find that different human segmentations of the same image are highly consistent. Use of this dataset is demonstrated in two applications: (1) evaluating the performance of segmentation algorithms and (2) measuring probability distributions associated with Gestalt grouping factors as well as statistics of image region properties.