Fix Eigen alignment issues for Eigen 3.3

src/base/camera_rig.h

@@ -23,6 +23,7 @@
 #include "base/camera.h"
 #include "base/pose.h"
 #include "base/reconstruction.h"
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/database_cache.h

@@ -29,6 +29,7 @@
 #include "base/database.h"
 #include "base/image.h"
 #include "base/scene_graph.h"
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/essential_matrix.h

@@ -23,6 +23,7 @@
 
 #include <ceres/ceres.h>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/feature.h

@@ -21,6 +21,7 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/feature_matching.h

@@ -24,6 +24,7 @@
 
 #include "base/database.h"
 #include "ext/SiftGPU/SiftGPU.h"
+#include "util/alignment.h"
 #include "util/cache.h"
 #include "util/opengl_utils.h"
 #include "util/threading.h"

src/base/feature_test.cc

@@ -19,6 +19,7 @@
 #include <boost/test/unit_test.hpp>
 
 #include "base/feature.h"
+#include "util/alignment.h"
 
 using namespace colmap;
 

src/base/gps.h

@@ -21,6 +21,7 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/homography_matrix.h

@@ -21,6 +21,7 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/image.h

@@ -25,6 +25,7 @@
 #include "base/camera.h"
 #include "base/point2d.h"
 #include "base/visibility_pyramid.h"
+#include "util/alignment.h"
 #include "util/logging.h"
 #include "util/math.h"
 #include "util/types.h"

src/base/pose.h

@@ -21,6 +21,7 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/pose_test.cc

@@ -152,7 +152,7 @@ BOOST_AUTO_TEST_CASE(TestAverageQuaternions) {
   std::vector<Eigen::Vector4d> qvecs;
   std::vector<double> weights;
 
-  qvecs = {ComposeIdentityQuaternion()};
+  qvecs = {{ComposeIdentityQuaternion()}};
   weights = {1.0};
   BOOST_CHECK_EQUAL(AverageQuaternions(qvecs, weights),
                     ComposeIdentityQuaternion());

src/base/reconstruction.h

@@ -29,6 +29,7 @@
 #include "base/point2d.h"
 #include "base/point3d.h"
 #include "base/track.h"
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/similarity_transform.h

@@ -22,6 +22,7 @@
 #include <Eigen/Core>
 #include <Eigen/Geometry>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {

src/base/triangulation.h

@@ -22,6 +22,7 @@
 #include <Eigen/Core>
 
 #include "base/camera.h"
+#include "util/alignment.h"
 #include "util/math.h"
 #include "util/types.h"
 

src/base/undistortion.h

@@ -18,6 +18,7 @@
 #define COLMAP_SRC_BASE_UNDISTORTION_H_
 
 #include "base/reconstruction.h"
+#include "util/alignment.h"
 #include "util/bitmap.h"
 #include "util/threading.h"
 

src/base/visibility_pyramid.h

@@ -21,6 +21,8 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
+
 namespace colmap {
 
 // A class that captures the distribution of points in a 2D grid.

src/base/warp.h

@@ -18,6 +18,7 @@
 #define COLMAP_SRC_BASE_WARP_H_
 
 #include "base/camera.h"
+#include "util/alignment.h"
 #include "util/bitmap.h"
 
 namespace colmap {

src/estimators/epnp.cc

@@ -32,10 +32,10 @@ std::vector<EPnPEstimator::M_t> EPnPEstimator::Estimate(
   EPnPEstimator epnp;
   M_t proj_matrix;
   if (!epnp.ComputePose(points2D, points3D, &proj_matrix)) {
-    return {};
+    return std::vector<EPnPEstimator::M_t>({});
   }
 
-  return {proj_matrix};
+  return std::vector<EPnPEstimator::M_t>({proj_matrix});
 }
 
 void EPnPEstimator::Residuals(const std::vector<X_t>& points2D,

src/estimators/epnp.h

@@ -22,6 +22,7 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {
@@ -47,7 +48,7 @@ class EPnPEstimator {
   typedef Eigen::Matrix3x4d M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 4; }
+  static const int kMinNumSamples = 4;
 
   // Estimate the most probable solution of the P3P problem from a set of
   // three 2D-3D point correspondences.

src/estimators/essential_matrix.h

@@ -23,6 +23,7 @@
 
 #include <ceres/ceres.h>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {
@@ -41,7 +42,7 @@ class EssentialMatrixFivePointEstimator {
   typedef Eigen::Matrix3d M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 5; }
+  static const int kMinNumSamples = 5;
 
   // Estimate up to 10 possible essential matrix solutions from a set of
   // corresponding points.
@@ -81,7 +82,7 @@ class EssentialMatrixEightPointEstimator {
   typedef Eigen::Matrix3d M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 8; }
+  static const int kMinNumSamples = 8;
 
   // Estimate essential matrix solutions from  set of corresponding points.
   //

src/estimators/euclidean_transform.h

@@ -18,6 +18,7 @@
 #define COLMAP_SRC_ESTIMATORS_EUCLIDEAN_TRANSFORM_H_
 
 #include "base/similarity_transform.h"
+#include "util/alignment.h"
 
 namespace colmap {
 

src/estimators/fundamental_matrix.h

@@ -22,6 +22,7 @@
 #include <Eigen/Core>
 
 #include "estimators/homography_matrix.h"
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {
@@ -41,7 +42,7 @@ class FundamentalMatrixSevenPointEstimator {
   typedef Eigen::Matrix3d M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 7; }
+  static const int kMinNumSamples = 7;
 
   // Estimate either 1 or 3 possible fundamental matrix solutions from a set of
   // corresponding points.
@@ -81,7 +82,7 @@ class FundamentalMatrixEightPointEstimator {
   typedef Eigen::Matrix3d M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 8; }
+  static const int kMinNumSamples = 8;
 
   // Estimate fundamental matrix solutions from a set of corresponding points.
   //

src/estimators/gp3p.cc

@@ -150,7 +150,7 @@ std::vector<Eigen::Vector3d> ComputeDepthsSylvester(
   Eigen::VectorXd roots_real;
   Eigen::VectorXd roots_imag;
   if (!FindPolynomialRootsCompanionMatrix(coeffs, &roots_real, &roots_imag)) {
-    return {};
+    return std::vector<Eigen::Vector3d>();
   }
 
   // Back-substitute every lambda_3 to the system of equations.
@@ -198,7 +198,7 @@ std::vector<GP3PEstimator::M_t> GP3PEstimator::Estimate(
   CHECK_EQ(points3D.size(), 3);
 
   if (CheckCollinearPoints(points3D[0], points3D[1], points3D[2])) {
-    return {};
+    return std::vector<GP3PEstimator::M_t>({});
   }
 
   // Transform 2D points into compact Pluecker line representation.
@@ -209,7 +209,7 @@ std::vector<GP3PEstimator::M_t> GP3PEstimator::Estimate(
 
   if (CheckParallelRays(plueckers[0].head<3>(), plueckers[1].head<3>(),
                         plueckers[2].head<3>())) {
-    return {};
+    return std::vector<GP3PEstimator::M_t>({});
   }
 
   // Compute the coefficients k1, k2, k3 using Eq. 4.
@@ -219,7 +219,7 @@ std::vector<GP3PEstimator::M_t> GP3PEstimator::Estimate(
   // Compute the depths along the Pluecker lines of the observations.
   const std::vector<Eigen::Vector3d> depths = ComputeDepthsSylvester(K);
   if (depths.empty()) {
-    return {};
+    return std::vector<GP3PEstimator::M_t>({});
   }
 
   // For all valid depth values, compute the transformation between points in

src/estimators/gp3p.h

@@ -21,6 +21,7 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {
@@ -34,23 +35,23 @@ namespace colmap {
 // This class is based on an original implementation by Federico Camposeco.
 class GP3PEstimator {
  public:
-  // The generalized image feature observations, which is composed of the
-  // relative pose of the specific camera in the generalized camera and its 2D
-  // image observation.
+  // The generalized image observations, which is composed of the relative pose
+  // of the specific camera in the generalized camera and its image observation.
   struct X_t {
     // The relative transformation from the generalized camera to the camera
     // frame of the observation.
-    Eigen::Matrix3x4d rel_tform;
+    Eigen::Matrix<double, 3, 4, Eigen::DontAlign> rel_tform;
     // The 2D image feature observation.
-    Eigen::Vector2d xy;
+    Eigen::Matrix<double, 2, 1, Eigen::DontAlign> xy;
   };
+
   // The observed 3D feature points in the world frame.
   typedef Eigen::Vector3d Y_t;
   // The transformation from the world to the generalized camera frame.
   typedef Eigen::Matrix3x4d M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 3; }
+  static const int kMinNumSamples = 3;
 
   // Estimate the most probable solution of the GP3P problem from a set of
   // three 2D-3D point correspondences.

src/estimators/homography_matrix.h

@@ -21,6 +21,7 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {
@@ -35,7 +36,7 @@ class HomographyMatrixEstimator {
   typedef Eigen::Matrix3d M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 4; }
+  static const int kMinNumSamples = 4;
 
   // Estimate the projective transformation (homography).
   //

src/estimators/p3p.cc

@@ -89,7 +89,7 @@ std::vector<P3PEstimator::M_t> P3PEstimator::Estimate(
   Eigen::VectorXd roots_real;
   Eigen::VectorXd roots_imag;
   if (!FindPolynomialRootsCompanionMatrix(coeffs, &roots_real, &roots_imag)) {
-    return {};
+    return std::vector<P3PEstimator::M_t>({});
   }
 
   std::vector<M_t> models;

src/estimators/p3p.h

@@ -21,6 +21,7 @@
 
 #include <Eigen/Core>
 
+#include "util/alignment.h"
 #include "util/types.h"
 
 namespace colmap {
@@ -42,7 +43,7 @@ class P3PEstimator {
   typedef Eigen::Matrix3x4d M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 3; }
+  static const int kMinNumSamples = 3;
 
   // Estimate the most probable solution of the P3P problem from a set of
   // three 2D-3D point correspondences.

src/estimators/pose.h

@@ -26,6 +26,7 @@
 #include "base/camera.h"
 #include "base/camera_models.h"
 #include "optim/loransac.h"
+#include "util/alignment.h"
 #include "util/logging.h"
 #include "util/threading.h"
 #include "util/types.h"

src/estimators/similarity_transform.h

@@ -23,6 +23,7 @@
 #include <Eigen/Geometry>
 
 #include "base/projection.h"
+#include "util/alignment.h"
 #include "util/logging.h"
 #include "util/types.h"
 
@@ -49,7 +50,7 @@ class SimilarityTransformEstimator {
   // The minimum number of samples needed to estimate a model. Note that
   // this only returns the true minimal sample in the two-dimensional case.
   // For higher dimensions, the system will alway be over-determined.
-  static size_t MinNumSamples() { return kDim; }
+  static const int kMinNumSamples = kDim;
 
   // Estimate the similarity transform.
   //

src/estimators/translation_transform.h

@@ -22,6 +22,7 @@
 #include <Eigen/Core>
 #include <Eigen/Geometry>
 
+#include "util/alignment.h"
 #include "util/logging.h"
 #include "util/types.h"
 
@@ -36,7 +37,7 @@ class TranslationTransformEstimator {
   typedef Eigen::Matrix<double, kDim, 1> M_t;
 
   // The minimum number of samples needed to estimate a model.
-  static size_t MinNumSamples() { return 1; }
+  static const int kMinNumSamples = 1;
 
   // Estimate the 2D translation transform.
   //