Hierarchical Planar Correlation Clustering for Cell Segmentation [chapter]

Julian Yarkony, Chong Zhang, Charless C. Fowlkes
2015 Lecture Notes in Computer Science  
We introduce a novel algorithm for hierarchical clustering on planar graphs we call "Hierarchical Greedy Planar Correlation Clustering" (HGPCC). We formulate hierarchical image segmentation as an ultrametric rounding problem on a superpixel graph where there are edges between superpixels that are adjacent in the image. We apply coordinate descent optimization where updates are based on planar correlation clustering. Planar correlation clustering is NP hard but the efficient Pla-narCC solver
more » ... ws for efficient and accurate approximate inference. We demonstrate HGPCC on problems in segmenting images of cells.
doi:10.1007/978-3-319-14612-6_36 fatcat:y6sv2qwtanabhpffitbtyr7wwy