Documentation of 'boofcv.alg.feature.describe.DescribePointSurfMod' Java class
DescribePointSurfMod
boofcv.alg.feature.describe

Class DescribePointSurfMod<II extends ImageGray>



  • public class DescribePointSurfMod<II extends ImageGray>
    extends DescribePointSurf<II>

    Modified SURF descriptor which attempts to smooth out edge conditions. Based upon MU-SURF described in [1] it computes features in over lapping sub-regions and has a separate set of weights for the large grid and for sub-regions. Due to these improvements it will in general produce better results than DescribePointSurf at the cost of additional computations.

    [1] M. Agrawal, K. Konolige, and M. Blas, "CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching," Computer Vision – ECCV 2008

    • Constructor Summary

      Constructors 
      Constructor and Description
      DescribePointSurfMod(java.lang.Class<II> imageType)
      Create a SURF-64 descriptor.
      DescribePointSurfMod(int widthLargeGrid, int widthSubRegion, int widthSample, int overLap, double sigmaLargeGrid, double sigmaSubRegion, boolean useHaar, java.lang.Class<II> imageType)
      Creates a SURF descriptor of arbitrary dimension by changing how the local region is sampled.
    • Constructor Detail

      • DescribePointSurfMod

        public DescribePointSurfMod(int widthLargeGrid,
                                    int widthSubRegion,
                                    int widthSample,
                                    int overLap,
                                    double sigmaLargeGrid,
                                    double sigmaSubRegion,
                                    boolean useHaar,
                                    java.lang.Class<II> imageType)
        Creates a SURF descriptor of arbitrary dimension by changing how the local region is sampled.
        Parameters:
        widthLargeGrid - Number of sub-regions wide the large grid is. Typically 4.
        widthSubRegion - Number of sample points wide a sub-region is. Typically 5.
        widthSample - The size of a sample point. Typically 3.
        overLap - Number of sample points sub-regions overlap, Typically 2.
        sigmaLargeGrid - Sigma used to weight points in the large grid. Typically 2.5
        sigmaSubRegion - Sigma used to weight points in the sub-region grid. Typically 2.5
        useHaar - If true the Haar wavelet will be used (what was used in [1]), false means an image gradient approximation will be used. True is recommended.
      • DescribePointSurfMod

        public DescribePointSurfMod(java.lang.Class<II> imageType)
        Create a SURF-64 descriptor. See [1] for details.
    • Method Detail

      • features

        public void features(double c_x,
                             double c_y,
                             double c,
                             double s,
                             double scale,
                             SparseImageGradient gradient,
                             double[] features)

        An improved SURF descriptor as presented in CenSurE paper. The sub-regions now overlap and more points are sampled in the sub-region to allow overlap.

        Overrides:
        features in class DescribePointSurf<II extends ImageGray>
        Parameters:
        c_x - Center of the feature x-coordinate.
        c_y - Center of the feature y-coordinate.
        c - cosine of the orientation
        s - sine of the orientation
        scale - The scale of the wavelets.
        features - Where the features are written to. Must be 4*(widthLargeGrid*widthSubRegion)^2 large.

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