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Minor documentation fixes
Change-Id: Ic531475acf2386b6f5839d2434bdcc1e4c730d14
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@@ -4,8 +4,10 @@
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Building Ceres Solver
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=====================
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Ceres source code and documentation are hosted at `code.google.com
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<http://code.google.com/p/ceres-solver/>`_.
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Stable Ceres Solver releases are available for download at
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`code.google.com <http://code.google.com/p/ceres-solver/>`_. For the
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more adventurous, the git repository is hosted on `Gerrit
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<https://ceres-solver-review.googlesource.com/>`_.
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.. _section-dependencies:
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@@ -37,7 +39,7 @@ strongly recommend building the library with gflags.
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5. `SuiteSparse
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<http://www.cise.ufl.edu/research/sparse/SuiteSparse/>`_ is used for
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sparse matrix analysis, ordering and factorization. In particular
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Ceres uses the AMD, COLAMD and CHOLMOD libraries. This is an optional
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Ceres uses the AMD, CAMD, COLAMD and CHOLMOD libraries. This is an optional
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dependency.
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6. `CXSparse <http://www.cise.ufl.edu/research/sparse/CXSparse/>`_ is
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@@ -92,8 +94,7 @@ platform. Start by installing all the dependencies.
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# protobuf
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sudo apt-get install libprotobuf-dev
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We are now ready to build and test Ceres. Note that ``CMake`` requires
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the exact path to the ``libglog.a`` and ``libgflag.a``.
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We are now ready to build and test Ceres.
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.. code-block:: bash
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@@ -110,8 +111,7 @@ dataset [Agarwal]_.
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.. code-block:: bash
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bin/simple_bundle_adjuster \
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../ceres-solver-1.6.0/data/problem-16-22106-pre.txt \
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bin/simple_bundle_adjuster ../ceres-solver-1.6.0/data/problem-16-22106-pre.txt
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This runs Ceres for a maximum of 10 iterations using the
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``DENSE_SCHUR`` linear solver. The output should look something like
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@@ -172,9 +172,10 @@ Building on Mac OS X
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====================
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On OS X, we recommend using the `homebrew
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<http://mxcl.github.com/homebrew/>`_ package manager. Start by
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installing all the dependencies. OS X ships with well optimized BLAS
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and LAPACK routines as part of the `vecLib
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<http://mxcl.github.com/homebrew/>`_ package manager to install the
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dependencies. There is no need to install ``BLAS`` or ``LAPACK``
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separately as OS X ships with optimized ``BLAS`` and ``LAPACK``
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routines as part of the `vecLib
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<https://developer.apple.com/library/mac/#documentation/Performance/Conceptual/vecLib/Reference/reference.html>`_
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framework.
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@@ -8,17 +8,9 @@ Solving nonlinear least squares problems [#f1]_ comes up in a broad
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range of areas across science and engineering - from fitting curves in
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statistics, to constructing 3D models from photographs in computer
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vision. Ceres Solver [#f2]_ [#f3]_ is a portable C++ library for
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solving non-linear least squares problems. It is designed to solve
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small and large sparse problems accurately and efficiently.
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solving non-linear least squares problems accurately and efficiently.
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At Google, Ceres Solver has been used for solving a variety of
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problems in computer vision and machine learning. e.g., it is used to
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to estimate the pose of Street View cars, aircrafts, and satellites;
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to build 3D models for PhotoTours; to estimate satellite image sensor
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characteristics, and more.
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Features:
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**Features**
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#. A friendly :ref:`chapter-modeling`.
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@@ -52,6 +44,17 @@ Features:
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underway.
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At Google, Ceres Solver has been used for solving a variety of
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problems in computer vision and machine learning. e.g., it is used to
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to estimate the pose of Street View cars, aircrafts, and satellites;
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to build 3D models for PhotoTours; to estimate satellite image sensor
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characteristics, and more.
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`Blender <http://www.blender.org>`_ uses Ceres for `motion tracking
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<http://mango.blender.org/development/planar-tracking-preview/>`_ and
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`bundle adjustment
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<http://wiki.blender.org/index.php/Dev:Ref/Release_Notes/2.67/Motion_Tracker>`_.
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.. rubric:: Footnotes
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