The maximum number of returned solutions

The maximum number of solutions returned by the estimator

The maximum number of solutions returned by the estimator

The maximum number of solutions that this algorithm returns

The maximum number of solutions that this algorithm returns

The maximum number of solutions returned by the estimator

The maximum number of solutions that this algorithm returns

The maximum number of solutions returned by the estimator

The maximum number of solutions that this algorithm returns

The maximum number of solutions returned by the solver

The maximum number of solutions returned by the estimator

The maximum number of solutions returned by the solver

The maximum number of solutions returned by the estimator

The maximum number of returned solutions

The maximum number of solutions returned by the solver

The maximum number of solutions returned by the estimator

The maximum number of solutions returned by the estimator

The maximum number of solutions returned by the estimator

Multiply two degree one polynomials of variables x, y, z. E.g. p1 = a[0]x + a[1]y + a[2]z + a[3] Output order: x^2 xy y^2 xz yz z^2 x y z 1 (GrevLex)

Multiply a 2 deg poly (in x, y, z) and a one deg poly in GrevLex order. x^3 x^2y xy^2 y^3 x^2z xyz y^2z xz^2 yz^2 z^3 x^2 xy y^2 xz yz z^2 x y z 1

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

It returns true/false depending on if the solver needs the gravity direction for the model estimation.

The size of a non-minimal sample required for the estimation

The size of a non-minimal sample required for the estimation

The size of a non-minimal sample required for the estimation

The size of a non-minimal sample required for the estimation

The size of a non-minimal sample required for the estimation

The size of a non-minimal sample required for the estimation

The size of a non-minimal sample required for the estimation

a, b are first order polys [x,y,z,1] c is degree 2 poly with order [ x^2, x*y, x*z, x, y^2, y*z, y, z^2, z, 1]

a is second degree poly with order [ x^2, x*y, x*z, x, y^2, y*z, y, z^2, z, 1] b is first degree with order [x y z 1] c is third degree with order (sa

The cells are ordered in ascending order along axes

Two cells are equal of their indices along all axes in both images are equal.

Nonsymmetric reduction to Hessenberg form.

Projection and distortion

Performs a few newton steps on the equations

If changed_list is not NULL while calling maxflow(), then the algorithm keeps a list of nodes which could potentially have changed their segmentation

Update the camera parameters such that the projections are rescaled