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Implementation of Koehl's method for calculating geometric moments #45

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brianthelion opened this issue Jun 2, 2014 · 3 comments
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@brianthelion
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The current method for calculating Zernike moments depends on first calculating the geometric moments for the mesh. This is the slowest step in the algorithm, by far.

The current implementation depends on a method due to Pozo that is O(N^6). Koehl proposes a recursive method that is O(N^3).

@brianthelion brianthelion self-assigned this Jun 2, 2014
@brianthelion
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I now have the method working and will focus on optimization.

@brianthelion
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Optimization is almost finished. I have reduced per-face computational time at N=20 from 0.20s (Pozo's method) to 0.01s (Koehl's method). Things are coming along nicely.

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Here are the latest benchmarks for Koehl's method on a standard Mindboggle mesh (~300k faces):

  • ~90 seconds at N=5 (vs. 360 seconds for Pozo)
  • ~3 minutes at N=10 (vs. 32 minutes for Pozo)
  • ~12 minutes at N=20 (vs. forever for Pozo)

Looking to push tomorrow.

binarybottle pushed a commit that referenced this issue Oct 4, 2014
…oments. This is the slowest step in calculating the Zernike moments. See Koehl (2012), IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 34, No. 11, pg 2158-2163.
binarybottle pushed a commit that referenced this issue Oct 4, 2014
…oments. This is the slowest step in calculating the Zernike moments. See Koehl (2012), IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 34, No. 11, pg 2158-2163.
binarybottle pushed a commit that referenced this issue Oct 4, 2014
…oments. This is the slowest step in calculating the Zernike moments. See Koehl (2012), IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 34, No. 11, pg 2158-2163.

Former-commit-id: 0bba48e
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