boofcv.alg.geo.f

Class FundamentalLinear7

java.lang.Object

boofcv.alg.geo.f.FundamentalLinear

boofcv.alg.geo.f.FundamentalLinear7

public class FundamentalLinear7
extends FundamentalLinear

Computes the essential or fundamental matrix using exactly 7 points with linear algebra. The number of required points is reduced from 8 to 7 by enforcing the singularity constraint, det(F) = 0. The number of solutions found is either one or three depending on the number of real roots found in the quadratic.

The computed fundamental matrix follow the following convention (with no noise) for the associated pair: x2^T*F*x1 = 0
x1 = keyLoc and x2 = currLoc.

References:

• R. Hartley, and A. Zisserman, "Multiple View Geometry in Computer Vision", 2nd Ed, Cambridge 2003

Author:

Peter Abeles

Field Summary

Fields

Modifier and Type	Field and Description
protected org.ejml.data.DenseMatrix64F	F1
protected org.ejml.data.DenseMatrix64F	F2

Fields inherited from class boofcv.alg.geo.f.FundamentalLinear

A, N1, N2, svdConstraints, svdNull, svdS, svdU, svdV, temp0

Constructor Summary

Constructors

Constructor and Description
FundamentalLinear7(boolean computeFundamental) When computing the essential matrix normalization is optional because pixel coordinates

Method Summary

Methods

Modifier and Type	Method and Description
static void	computeCoefficients(org.ejml.data.DenseMatrix64F F1, org.ejml.data.DenseMatrix64F F2, double[] coefs) Computes the coefficients such that the following is true: det(&alpha*F1 + (1-α)*F2 ) = c0 + c1*α + c2*α2 + c2*α3
static void	computeCoefficients(org.ejml.data.DenseMatrix64F F1, org.ejml.data.DenseMatrix64F F2, int i, int j, int k, double[] coefs, boolean minus)
static void	computeCoefficients(double x1, double y1, double z1, double x2, double y2, double z2, double[] coefs)
static void	computeCoefficientsMinus(double x1, double y1, double z1, double x2, double y2, double z2, double[] coefs)
void	computeSolutions(org.ddogleg.struct.FastQueue<org.ejml.data.DenseMatrix64F> solutions) Find the polynomial roots and for each root compute the Fundamental matrix.
boolean	process(List<AssociatedPair> points, org.ddogleg.struct.FastQueue<org.ejml.data.DenseMatrix64F> solutions) Computes a fundamental or essential matrix from a set of associated point correspondences.

Methods inherited from class boofcv.alg.geo.f.FundamentalLinear

createA, getSvdS, getSvdU, getSvdV, isComputeFundamental, projectOntoEssential, projectOntoFundamentalSpace, undoNormalizationF

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

F1

protected org.ejml.data.DenseMatrix64F F1

F2

protected org.ejml.data.DenseMatrix64F F2

Constructor Detail

FundamentalLinear7

public FundamentalLinear7(boolean computeFundamental)

When computing the essential matrix normalization is optional because pixel coordinates

Parameters:

computeFundamental - true it computes a fundamental matrix and false for essential

Method Detail

process

public boolean process(List<AssociatedPair> points,
              org.ddogleg.struct.FastQueue<org.ejml.data.DenseMatrix64F> solutions)

Computes a fundamental or essential matrix from a set of associated point correspondences.

Parameters:

points - Input: List of corresponding image coordinates. In pixel for fundamental matrix or normalized coordinates for essential matrix.

solutions - Output: Storage for the found solutions.

Returns:

true If successful or false if it failed

computeSolutions

public void computeSolutions(org.ddogleg.struct.FastQueue<org.ejml.data.DenseMatrix64F> solutions)

Find the polynomial roots and for each root compute the Fundamental matrix. Given the two matrices it will compute an alpha such that the determinant is zero.
det(&alpha*F1 + (1-α)*F2 ) = 0

computeCoefficients

public static void computeCoefficients(org.ejml.data.DenseMatrix64F F1,
                       org.ejml.data.DenseMatrix64F F2,
                       double[] coefs)

Computes the coefficients such that the following is true:
det(&alpha*F1 + (1-α)*F2 ) = c₀ + c₁*α + c₂*α² + c₂*α³

Parameters:

F1 - a fundamental matrix

F2 - a fundamental matrix

coefs - Where results are returned.

computeCoefficients

public static void computeCoefficients(org.ejml.data.DenseMatrix64F F1,
                       org.ejml.data.DenseMatrix64F F2,
                       int i,
                       int j,
                       int k,
                       double[] coefs,
                       boolean minus)

computeCoefficients

public static void computeCoefficients(double x1,
                       double y1,
                       double z1,
                       double x2,
                       double y2,
                       double z2,
                       double[] coefs)

computeCoefficientsMinus

public static void computeCoefficientsMinus(double x1,
                            double y1,
                            double z1,
                            double x2,
                            double y2,
                            double z2,
                            double[] coefs)