5 files changed, 27 insertions, 11 deletions

diff --git a/extern/libmv/libmv/multiview/euclidean_resection.cc b/extern/libmv/libmv/multiview/euclidean_resection.cc
index bcde6de5cab..6cad4cac049 100644
--- a/extern/libmv/libmv/multiview/euclidean_resection.cc
+++ b/extern/libmv/libmv/multiview/euclidean_resection.cc
@@ -535,7 +535,16 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera,
   vector<Vec3> ts(3);
   Vec rmse(3);
 
-  // TODO(julien): Document where the "1e-3" magical constant comes from below.
+  // At one point this threshold was 1e-3, and caused no end of problems in
+  // Blender by causing frames to not resect when they would have worked fine.
+  // When the resect failed, the projective followup is run leading to worse
+  // results, and often the dreaded "flipping" where objects get flipped
+  // between frames. Instead, disable the check for now, always succeeding. The
+  // ultimate check is always reprojection error anyway.
+  //
+  // TODO(keir): Decide if setting this to infinity, effectively disabling the
+  // check, is the right approach. So far this seems the case.
+  double kSuccessThreshold = std::numeric_limits<double>::max();
 
   // Find the first possible solution for R, t corresponding to:
   // Betas          = [b00 b01 b11 b02 b12 b22 b03 b13 b23 b33]
@@ -548,7 +557,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera,
   Eigen::JacobiSVD<Mat> svd_of_l4(l_6x4, 
                                   Eigen::ComputeFullU | Eigen::ComputeFullV);
   Vec4 b4 = svd_of_l4.solve(rho);
-  if ((l_6x4 * b4).isApprox(rho, 1e-3)) {
+  if ((l_6x4 * b4).isApprox(rho, kSuccessThreshold)) {
     if (b4(0) < 0) {
       b4 = -b4;
     } 
@@ -574,7 +583,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera,
   Vec3 b3 = svdOfL3.solve(rho);
   VLOG(2) << " rho = " << rho;
   VLOG(2) << " l_6x3 * b3 = " << l_6x3 * b3;
-  if ((l_6x3 * b3).isApprox(rho, 1e-3)) {
+  if ((l_6x3 * b3).isApprox(rho, kSuccessThreshold)) {
     if (b3(0) < 0) {
       betas(0) = std::sqrt(-b3(0));
       betas(1) = (b3(2) < 0) ? std::sqrt(-b3(2)) : 0;
@@ -605,7 +614,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera,
   Eigen::JacobiSVD<Mat> svdOfL5(l_6x5, 
                                 Eigen::ComputeFullU | Eigen::ComputeFullV);
   Vec5 b5 = svdOfL5.solve(rho);
-  if ((l_6x5 * b5).isApprox(rho, 1e-3)) {
+  if ((l_6x5 * b5).isApprox(rho, kSuccessThreshold)) {
     if (b5(0) < 0) {
       betas(0) = std::sqrt(-b5(0));
       if (b5(2) < 0) {
diff --git a/extern/libmv/libmv/multiview/euclidean_resection.h b/extern/libmv/libmv/multiview/euclidean_resection.h
index 08fa3d90bd3..f20513d3fbe 100644
--- a/extern/libmv/libmv/multiview/euclidean_resection.h
+++ b/extern/libmv/libmv/multiview/euclidean_resection.h
@@ -29,6 +29,9 @@ namespace euclidean_resection {
   
 enum ResectionMethod {
   RESECTION_ANSAR_DANIILIDIS,
+
+  // The "EPnP" algorithm by Lepetit et al.
+  // http://cvlab.epfl.ch/~lepetit/papers/lepetit_ijcv08.pdf
   RESECTION_EPNP,
 };
 
diff --git a/extern/libmv/libmv/numeric/levenberg_marquardt.h b/extern/libmv/libmv/numeric/levenberg_marquardt.h
index 4473b72f156..a7877e0270b 100644
--- a/extern/libmv/libmv/numeric/levenberg_marquardt.h
+++ b/extern/libmv/libmv/numeric/levenberg_marquardt.h
@@ -124,11 +124,11 @@ class LevenbergMarquardt {
     Parameters dx, x_new;
     int i;
     for (i = 0; results.status == RUNNING && i < params.max_iterations; ++i) {
-      VLOG(1) << "iteration: " << i;
-      VLOG(1) << "||f(x)||: " << f_(x).norm();
-      VLOG(1) << "max(g): " << g.array().abs().maxCoeff();
-      VLOG(1) << "u: " << u;
-      VLOG(1) << "v: " << v;
+      VLOG(3) << "iteration: " << i;
+      VLOG(3) << "||f(x)||: " << f_(x).norm();
+      VLOG(3) << "max(g): " << g.array().abs().maxCoeff();
+      VLOG(3) << "u: " << u;
+      VLOG(3) << "v: " << v;
 
       AMatrixType A_augmented = A + u*AMatrixType::Identity(J.cols(), J.cols());
       Solver solver(A_augmented);
diff --git a/extern/libmv/libmv/simple_pipeline/pipeline.cc b/extern/libmv/libmv/simple_pipeline/pipeline.cc
index 2459d059114..4773a70d69b 100644
--- a/extern/libmv/libmv/simple_pipeline/pipeline.cc
+++ b/extern/libmv/libmv/simple_pipeline/pipeline.cc
@@ -242,9 +242,9 @@ void InternalCompleteReconstruction(
                                        (double)tot_resects/(max_image));
       if (PipelineRoutines::Resect(reconstructed_markers, reconstruction, true)) {
         num_resects++;
-        LG << "Ran Resect() for image " << image;
+        LG << "Ran final Resect() for image " << image;
       } else {
-        LG << "Failed Resect() for image " << image;
+        LG << "Failed final Resect() for image " << image;
       }
     }
   }
diff --git a/extern/libmv/libmv/simple_pipeline/resect.cc b/extern/libmv/libmv/simple_pipeline/resect.cc
index b30238f7e39..8737182dd43 100644
--- a/extern/libmv/libmv/simple_pipeline/resect.cc
+++ b/extern/libmv/libmv/simple_pipeline/resect.cc
@@ -108,6 +108,10 @@ bool EuclideanResect(const vector<Marker> &markers,
     // printf("Resection for image %d failed\n", markers[0].image);
     LG << "Resection for image " << markers[0].image << " failed;"
        << " trying fallback projective resection.";
+
+    LG << "No fallback; failing resection for " << markers[0].image;
+    return false;
+
     if (!final_pass) return false;
     // Euclidean resection failed. Fall back to projective resection, which is
     // less reliable but better conditioned when there are many points.