Содержание
- 2. Where in the world is Lak? Thanks to Don MacGorman, Will Agent & Madison Miller for
- 3. The common approach Objects identified based on a threshold All pixels above threshold are part of
- 4. Problem: threshold is global Same threshold does not work for initiating vs. mature storms
- 5. Example of threshold problem
- 6. Problem: Association is final Association takes only two frames into account Bad decisions percolate
- 7. Example of association problem
- 8. Premise … Try to avoid hard decisions Use locally adaptive thresholds to identify storms Based on
- 9. Enhanced Watershed Transform Start from local peak Grow till specified size is reached In effect, we
- 10. EWT Example
- 11. Multiple Hypotheses Tracking (MHT) MHT is based on two useful algorithms: Hungarian Method or Munkres algorithm
- 12. MHT In practice, will lead to combinatorial explosion So, prune to keep around only K total
- 13. EWT and MHT in QC of Az-Shear Azimuthal Shear a very noisy field Rotation tracks (accumulation
- 14. Rotation Tracks Cleanup
- 15. Summary Can avoid/postpone hard decisions in tracking Use locally adaptive thresholds to identify storms Paper in
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