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285 lines
11 KiB
285 lines
11 KiB
// David Eberly, Geometric Tools, Redmond WA 98052
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// Copyright (c) 1998-2021
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// Distributed under the Boost Software License, Version 1.0.
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// https://www.boost.org/LICENSE_1_0.txt
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// https://www.geometrictools.com/License/Boost/LICENSE_1_0.txt
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// Version: 4.0.2019.08.13
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#pragma once
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#include <Mathematics/Matrix2x2.h>
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#include <Mathematics/Matrix3x3.h>
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// The MeshCurvature class estimates principal curvatures and principal
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// directions at the vertices of a manifold triangle mesh. The algorithm
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// is described in
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// https://www.geometrictools.com/Documentation/MeshDifferentialGeometry.pdf
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namespace gte
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{
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template <typename Real>
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class MeshCurvature
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{
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public:
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MeshCurvature() = default;
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// The input to operator() is a triangle mesh with the specified
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// vertex buffer and index buffer. The number of elements of
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// 'indices' must be a multiple of 3, each triple of indices
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// (3*t, 3*t+1, 3*t+2) representing the triangle with vertices
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// (vertices[3*t], vertices[3*t+1], vertices[3*t+2]). The
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// singularity threshold is a small nonnegative number. It is
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// used to characterize whether the DWTrn matrix is singular. In
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// theory, set the threshold to zero. In practice you might have
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// to set this to a small positive number.
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void operator()(
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size_t numVertices, Vector3<Real> const* vertices,
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size_t numTriangles, unsigned int const* indices,
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Real singularityThreshold)
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{
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mNormals.resize(numVertices);
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mMinCurvatures.resize(numVertices);
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mMaxCurvatures.resize(numVertices);
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mMinDirections.resize(numVertices);
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mMaxDirections.resize(numVertices);
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// Compute the normal vectors for the vertices as an
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// area-weighted sum of the triangles sharing a vertex.
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Vector3<Real> vzero{ (Real)0, (Real)0, (Real)0 };
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std::fill(mNormals.begin(), mNormals.end(), vzero);
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unsigned int const* currentIndex = indices;
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for (size_t i = 0; i < numTriangles; ++i)
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{
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// Get vertex indices.
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unsigned int v0 = *currentIndex++;
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unsigned int v1 = *currentIndex++;
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unsigned int v2 = *currentIndex++;
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// Compute the normal (length provides a weighted sum).
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Vector3<Real> edge1 = vertices[v1] - vertices[v0];
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Vector3<Real> edge2 = vertices[v2] - vertices[v0];
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Vector3<Real> normal = Cross(edge1, edge2);
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mNormals[v0] += normal;
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mNormals[v1] += normal;
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mNormals[v2] += normal;
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}
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for (size_t i = 0; i < numVertices; ++i)
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{
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Normalize(mNormals[i]);
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}
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// Compute the matrix of normal derivatives.
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Matrix3x3<Real> mzero;
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std::vector<Matrix3x3<Real>> DNormal(numVertices, mzero);
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std::vector<Matrix3x3<Real>> WWTrn(numVertices, mzero);
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std::vector<Matrix3x3<Real>> DWTrn(numVertices, mzero);
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std::vector<bool> DWTrnZero(numVertices, false);
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currentIndex = indices;
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for (size_t i = 0; i < numTriangles; ++i)
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{
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// Get vertex indices.
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unsigned int v[3];
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v[0] = *currentIndex++;
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v[1] = *currentIndex++;
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v[2] = *currentIndex++;
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for (size_t j = 0; j < 3; j++)
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{
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unsigned int v0 = v[j];
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unsigned int v1 = v[(j + 1) % 3];
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unsigned int v2 = v[(j + 2) % 3];
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// Compute the edge direction from vertex v0 to vertex v1,
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// project it to the tangent plane of vertex v0 and
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// compute the difference of adjacent normals.
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Vector3<Real> E = vertices[v1] - vertices[v0];
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Vector3<Real> W = E - Dot(E, mNormals[v0]) * mNormals[v0];
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Vector3<Real> D = mNormals[v1] - mNormals[v0];
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for (int row = 0; row < 3; ++row)
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{
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for (int col = 0; col < 3; ++col)
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{
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WWTrn[v0](row, col) += W[row] * W[col];
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DWTrn[v0](row, col) += D[row] * W[col];
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}
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}
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// Compute the edge direction from vertex v0 to vertex v2,
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// project it to the tangent plane of vertex v0 and
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// compute the difference of adjacent normals.
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E = vertices[v2] - vertices[v0];
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W = E - Dot(E, mNormals[v0]) * mNormals[v0];
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D = mNormals[v2] - mNormals[v0];
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for (int row = 0; row < 3; ++row)
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{
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for (int col = 0; col < 3; ++col)
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{
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WWTrn[v0](row, col) += W[row] * W[col];
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DWTrn[v0](row, col) += D[row] * W[col];
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}
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}
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}
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}
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// Add in N*N^T to W*W^T for numerical stability. In theory 0*0^T
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// is added to D*W^T, but of course no update is needed in the
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// implementation. Compute the matrix of normal derivatives.
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for (size_t i = 0; i < numVertices; ++i)
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{
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for (int row = 0; row < 3; ++row)
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{
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for (int col = 0; col < 3; ++col)
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{
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WWTrn[i](row, col) = (Real)0.5 * WWTrn[i](row, col) +
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mNormals[i][row] * mNormals[i][col];
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DWTrn[i](row, col) *= (Real)0.5;
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}
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}
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// Compute the max-abs entry of D*W^T. If this entry is
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// (nearly) zero, flag the DNormal matrix as singular.
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Real maxAbs = (Real)0;
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for (int row = 0; row < 3; ++row)
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{
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for (int col = 0; col < 3; ++col)
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{
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Real absEntry = std::fabs(DWTrn[i](row, col));
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if (absEntry > maxAbs)
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{
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maxAbs = absEntry;
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}
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}
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}
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if (maxAbs < singularityThreshold)
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{
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DWTrnZero[i] = true;
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}
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DNormal[i] = DWTrn[i] * Inverse(WWTrn[i]);
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}
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// If N is a unit-length normal at a vertex, let U and V be
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// unit-length tangents so that {U, V, N} is an orthonormal set.
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// Define the matrix J = [U | V], a 3-by-2 matrix whose columns
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// are U and V. Define J^T to be the transpose of J, a 2-by-3
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// matrix. Let dN/dX denote the matrix of first-order derivatives
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// of the normal vector field. The shape matrix is
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// S = (J^T * J)^{-1} * J^T * dN/dX * J = J^T * dN/dX * J
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// where the superscript of -1 denotes the inverse; the formula
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// allows for J to be created from non-perpendicular vectors. The
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// matrix S is 2-by-2. The principal curvatures are the
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// eigenvalues of S. If k is a principal curvature and W is the
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// 2-by-1 eigenvector corresponding to it, then S*W = k*W (by
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// definition). The corresponding 3-by-1 tangent vector at the
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// vertex is a principal direction for k and is J*W.
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for (size_t i = 0; i < numVertices; ++i)
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{
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// Compute U and V given N.
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Vector3<Real> basis[3];
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basis[0] = mNormals[i];
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ComputeOrthogonalComplement(1, basis);
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Vector3<Real> const& U = basis[1];
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Vector3<Real> const& V = basis[2];
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if (DWTrnZero[i])
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{
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// At a locally planar point.
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mMinCurvatures[i] = (Real)0;
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mMaxCurvatures[i] = (Real)0;
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mMinDirections[i] = U;
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mMaxDirections[i] = V;
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continue;
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}
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// Compute S = J^T * dN/dX * J. In theory S is symmetric, but
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// because dN/dX is estimated, we must ensure that the
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// computed S is symmetric.
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Real s00 = Dot(U, DNormal[i] * U);
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Real s01 = Dot(U, DNormal[i] * V);
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Real s10 = Dot(V, DNormal[i] * U);
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Real s11 = Dot(V, DNormal[i] * V);
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Real avr = (Real)0.5 * (s01 + s10);
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Matrix2x2<Real> S{ s00, avr, avr, s11 };
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// Compute the eigenvalues of S (min and max curvatures).
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Real trace = S(0, 0) + S(1, 1);
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Real det = S(0, 0) * S(1, 1) - S(0, 1) * S(1, 0);
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Real discr = trace * trace - (Real)4.0 * det;
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Real rootDiscr = std::sqrt(std::max(discr, (Real)0));
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mMinCurvatures[i] = (Real)0.5* (trace - rootDiscr);
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mMaxCurvatures[i] = (Real)0.5* (trace + rootDiscr);
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// Compute the eigenvectors of S.
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Vector2<Real> W0{ S(0, 1), mMinCurvatures[i] - S(0, 0) };
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Vector2<Real> W1{ mMinCurvatures[i] - S(1, 1), S(1, 0) };
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if (Dot(W0, W0) >= Dot(W1, W1))
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{
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Normalize(W0);
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mMinDirections[i] = W0[0] * U + W0[1] * V;
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}
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else
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{
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Normalize(W1);
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mMinDirections[i] = W1[0] * U + W1[1] * V;
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}
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W0 = Vector2<Real>{ S(0, 1), mMaxCurvatures[i] - S(0, 0) };
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W1 = Vector2<Real>{ mMaxCurvatures[i] - S(1, 1), S(1, 0) };
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if (Dot(W0, W0) >= Dot(W1, W1))
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{
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Normalize(W0);
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mMaxDirections[i] = W0[0] * U + W0[1] * V;
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}
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else
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{
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Normalize(W1);
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mMaxDirections[i] = W1[0] * U + W1[1] * V;
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}
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}
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}
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void operator()(
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std::vector<Vector3<Real>> const& vertices,
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std::vector<unsigned int> const& indices,
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Real singularityThreshold)
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{
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operator()(vertices.size(), vertices.data(), indices.size() / 3,
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indices.data(), singularityThreshold);
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}
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inline std::vector<Vector3<Real>> const& GetNormals() const
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{
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return mNormals;
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}
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inline std::vector<Real> const& GetMinCurvatures() const
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{
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return mMinCurvatures;
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}
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inline std::vector<Real> const& GetMaxCurvatures() const
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{
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return mMaxCurvatures;
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}
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inline std::vector<Vector3<Real>> const& GetMinDirections() const
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{
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return mMinDirections;
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}
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inline std::vector<Vector3<Real>> const& GetMaxDirections() const
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{
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return mMaxDirections;
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}
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private:
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std::vector<Vector3<Real>> mNormals;
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std::vector<Real> mMinCurvatures;
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std::vector<Real> mMaxCurvatures;
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std::vector<Vector3<Real>> mMinDirections;
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std::vector<Vector3<Real>> mMaxDirections;
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};
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}
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