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Evaluation Report on Point Matching Strategies Across Five Data Sets

This report summarizes the findings of the point matching evaluation conducted by Motaz Semir and Howard. We analyzed five distinct data sets (A, B, C, D, E), each subjected to 20 tests to calculate the average accuracy rates. The final grade for each set was determined by the mean accuracy across all tests, with a tiebreaker based on average execution time. Detailed tables present the results from multiple experiments, highlighting key performance indicators, and recognizing the top performers: Feipeng Zhao, Bernardo F. Juncal, and An Dang.

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Evaluation Report on Point Matching Strategies Across Five Data Sets

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  1. Point Matching Evaluation Report Motaz Semir Howard

  2. Grading Strategy • 5 data sets: A,B,C,D,E • For each data set: run 20 tests and average the acc rates • Final grade: average acc rate of 5 data sets • Tiebreaker is Average Time

  3. Experiment 1 PointMatchingA

  4. Table: A Red circle: highest accuracy rate Blue circle: shortest running time when acc > 0.9

  5. Experiment 2 PointMatchingB

  6. Table: A,B

  7. Experiment 3 PointMatchingC

  8. Table: A,B,C

  9. Experiment 4 PointMatchingD

  10. Table: A,B,C,D

  11. Experiment 5 PointMatchingE

  12. Table: A,B,C,D,E

  13. Table: A,B,C,D,E,Avg Acc Table:

  14. Winners: Alpha: Feipeng Zhao Bernardo F. Juncal An Dang

  15. Thank You

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