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  /external/eigen/scripts/
eigen_gen_docs 16 rsync -az --no-p --delete build/doc/html/ $USER@ssh.tuxfamily.org:eigen/eigen.tuxfamily.org-web/htdocs/dox-devel/ || { echo "upload failed"; exit 1; }
19 ssh $USER@ssh.tuxfamily.org 'chmod -R g+w /home/eigen/eigen.tuxfamily.org-web/htdocs/dox-devel' || { echo "perm failed"; exit 1; }
  /external/ceres-solver/internal/ceres/
generate_eliminator_specialization.py 87 #include "ceres/internal/eigen.h"
114 #include "ceres/internal/eigen.h"
  /external/ceres-solver/docs/
build.tex 12 \item{\eigen~\footnote{\url{http://eigen.tuxfamily.org}}} is used for doing all the low level matrix and
72 \item{\eigen}
163 \item{\eigen}
165 brew install eigen
198 (\texttt{ceres/eigen}, \texttt{ceres/glog}, etc)
200 \item Eigen 3.1 from eigen.tuxfamily.org (needed on Windows; 3.0.x will not
283 \eigen, \gflags\ and \glog.
294 \eigen, \gflags\ and \glog
    [all...]
ceres-solver.tex 80 \newcommand{\eigen}{\texttt{Eigen3}}
introduction.tex 6 The key computational cost when solving a non-linear least squares problem is the solution of a linear least squares problem in each iteration. To this end Ceres supports a number of different linear solvers suited for different needs. This includes dense QR factorization (using \eigen) for small scale problems, sparse Cholesky factorization (using \texttt{SuiteSparse}) for general sparse problems and specialized Schur complement based solvers for problems that arise in multi-view geometry~\cite{hartley-zisserman-book-2004}.
  /external/jmonkeyengine/engine/src/core/com/jme3/util/
TempVars.java 196 * Eigen
198 public final Eigen3f eigen = new Eigen3f(); field in class:TempVars
  /external/ceres-solver/
Android.mk 13 external/eigen
  /external/jmonkeyengine/engine/src/core/com/jme3/math/
Line.java 140 Eigen3f compEigen1 = vars.eigen;
171 //find the smallest eigen vector for the direction vector

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