Support-weighted partial recentering of maxmin seeds using halfspace depth yields consistent geometric improvement over standard maxmin in planar benchmarks while preserving thresholded H1 summaries.
Exploring uses of persistent homology for statistical analysis of landmark-based shape data.Journal of Multivariate Analysis, 101(9):2184–2199
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Local Depth-Based Corrections to Maxmin Landmark Selection for Lazy Witness Persistence
Support-weighted partial recentering of maxmin seeds using halfspace depth yields consistent geometric improvement over standard maxmin in planar benchmarks while preserving thresholded H1 summaries.