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Hierarchical Segmentation Using Tree-Based Shape Spaces
2017
IEEE Transactions on Pattern Analysis and Machine Intelligence
Current trends in image segmentation are to compute a hierarchy of image segmentations from fine to coarse. A classical approach to obtain a single meaningful image partition from a given hierarchy is to cut it in an optimal way, following the seminal approach of the scale-set theory. While interesting in many cases, the resulting segmentation, being a non-horizontal cut, is limited by the structure of the hierarchy. In this paper, we propose a novel approach that acts by transforming an input
doi:10.1109/tpami.2016.2554550
pmid:27101599
fatcat:jd6p3i743zdapdezd7u6t7benm