diff options
author | Dan Koschier <dankosc> | 2019-06-17 19:35:18 +0300 |
---|---|---|
committer | Brecht Van Lommel <brechtvanlommel@gmail.com> | 2019-06-17 19:53:49 +0300 |
commit | 4cc98af3a4413129fa7c5088532433ce6e9b3e81 (patch) | |
tree | 98b99b940713c993e932290ba23dfe251820f8fd /intern | |
parent | 538f2aeaefb0272da66a921cf0ed9aad30f09206 (diff) |
Fix T53581: remesh modifier artifacts in sharp mode
Replace relative threshold for pseudo inverse in sharp remeshing modifier with
0.1 as proposed in the original paper.
Also change pseudo-inverse implementation that works with dynamic heap-allocated
matrix to static 3x3 version, for performance
Differential Revision: https://developer.blender.org/D5078
Diffstat (limited to 'intern')
-rw-r--r-- | intern/dualcon/intern/octree.cpp | 18 |
1 files changed, 6 insertions, 12 deletions
diff --git a/intern/dualcon/intern/octree.cpp b/intern/dualcon/intern/octree.cpp index a6fac6fed33..70b3b8bb457 100644 --- a/intern/dualcon/intern/octree.cpp +++ b/intern/dualcon/intern/octree.cpp @@ -2180,19 +2180,13 @@ void Octree::countIntersection(Node *node, int height, int &nedge, int &ncell, i } /* from http://eigen.tuxfamily.org/bz/show_bug.cgi?id=257 */ -template<typename _Matrix_Type_> -void pseudoInverse(const _Matrix_Type_ &a, - _Matrix_Type_ &result, - double epsilon = std::numeric_limits<typename _Matrix_Type_::Scalar>::epsilon()) +static void pseudoInverse(const Eigen::Matrix3f &a, Eigen::Matrix3f &result, float tolerance) { - Eigen::JacobiSVD<_Matrix_Type_> svd = a.jacobiSvd(Eigen::ComputeFullU | Eigen::ComputeFullV); - - typename _Matrix_Type_::Scalar tolerance = epsilon * std::max(a.cols(), a.rows()) * - svd.singularValues().array().abs().maxCoeff(); + Eigen::JacobiSVD<Eigen::Matrix3f> svd = a.jacobiSvd(Eigen::ComputeFullU | Eigen::ComputeFullV); result = svd.matrixV() * - _Matrix_Type_((svd.singularValues().array().abs() > tolerance) - .select(svd.singularValues().array().inverse(), 0)) + Eigen::Vector3f((svd.singularValues().array().abs() > tolerance) + .select(svd.singularValues().array().inverse(), 0)) .asDiagonal() * svd.matrixU().adjoint(); } @@ -2203,9 +2197,9 @@ static void solve_least_squares(const float halfA[], float rvalue[]) { /* calculate pseudo-inverse */ - Eigen::MatrixXf A(3, 3), pinv(3, 3); + Eigen::Matrix3f A, pinv; A << halfA[0], halfA[1], halfA[2], halfA[1], halfA[3], halfA[4], halfA[2], halfA[4], halfA[5]; - pseudoInverse(A, pinv); + pseudoInverse(A, pinv, 0.1f); Eigen::Vector3f b2(b), mp(midpoint), result; b2 = b2 + A * -mp; |