121 lines
5.6 KiB
C++
121 lines
5.6 KiB
C++
/******************************************************************************
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* Author: Laurent Kneip *
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* Contact: kneip.laurent@gmail.com *
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* License: Copyright (c) 2013 Laurent Kneip, ANU. All rights reserved. *
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* *
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* Redistribution and use in source and binary forms, with or without *
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* modification, are permitted provided that the following conditions *
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* are met: *
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* * Redistributions of source code must retain the above copyright *
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* notice, this list of conditions and the following disclaimer. *
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* * Redistributions in binary form must reproduce the above copyright *
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* notice, this list of conditions and the following disclaimer in the *
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* documentation and/or other materials provided with the distribution. *
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* * Neither the name of ANU nor the names of its contributors may be *
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* used to endorse or promote products derived from this software without *
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* specific prior written permission. *
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* *
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"*
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE *
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE *
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* ARE DISCLAIMED. IN NO EVENT SHALL ANU OR THE CONTRIBUTORS BE LIABLE *
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL *
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR *
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* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER *
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT *
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY *
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* OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF *
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* SUCH DAMAGE. *
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******************************************************************************/
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/**
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* \file point_cloud/methods.hpp
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* \brief Methods for computing the transformation between two frames that
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* contain point-clouds.
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*/
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#ifndef OPENGV_POINT_CLOUD_METHODS_HPP_
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#define OPENGV_POINT_CLOUD_METHODS_HPP_
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#include <stdlib.h>
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#include <vector>
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#include <opengv/types.hpp>
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#include <opengv/point_cloud/PointCloudAdapterBase.hpp>
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/**
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* \brief The namespace of this library.
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*/
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namespace opengv
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{
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/**
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* \brief The namespace for the point-cloud alignment methods.
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*/
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namespace point_cloud
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{
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/**
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* \brief Compute the transformation between two frames containing point clouds,
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* following Arun's method [13]. Using all available correspondences.
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*
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* \param[in] adapter Visitor holding world-point correspondences.
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* \return Transformation from frame 2 back to frame 1 (
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* \f$ \mathbf{T} = \left(\begin{array}{cc} \mathbf{R} & \mathbf{t} \end{array}\right) \f$,
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* with \f$ \mathbf{t} \f$ being the position of frame 2 seen from
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* frame 1, and \f$ \mathbf{R} \f$ being the rotation from
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* frame 2 to frame 1).
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*/
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transformation_t threept_arun( const PointCloudAdapterBase & adapter );
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/**
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* \brief Compute the transformation between two frames containing point clouds,
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* following Arun's method [13].
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*
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* \param[in] adapter Visitor holding world-point correspondences.
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* \param[in] indices Indices of the correspondences used for deriving the
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* transformation.
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* \return Transformation from frame 2 back to frame 1 (
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* \f$ \mathbf{T} = \left(\begin{array}{cc} \mathbf{R} & \mathbf{t} \end{array}\right) \f$,
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* with \f$ \mathbf{t} \f$ being the position of frame 2 seen from
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* frame 1, and \f$ \mathbf{R} \f$ being the rotation from
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* frame 2 to frame 1).
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*/
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transformation_t threept_arun(
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const PointCloudAdapterBase & adapter,
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const std::vector<int> & indices );
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/**
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* \brief Compute the transformation between two frames containing point clouds
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* using nonlinear optimization. Using all available correspondences.
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*
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* \param[in] adapter Visitor holding world-point correspondences, plus the
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* initial values.
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* \return Transformation from frame 2 back to frame 1 (
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* \f$ \mathbf{T} = \left(\begin{array}{cc} \mathbf{R} & \mathbf{t} \end{array}\right) \f$,
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* with \f$ \mathbf{t} \f$ being the position of frame 2 seen from
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* frame 1, and \f$ \mathbf{R} \f$ being the rotation from
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* frame 2 to frame 1).
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*/
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transformation_t optimize_nonlinear( PointCloudAdapterBase & adapter );
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/**
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* \brief Compute the transformation between two frames containing point clouds.
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* Using nonlinear optimization.
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*
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* \param[in] adapter Visitor holding world-point correspondences, plus the
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* initial values.
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* \param[in] indices Indices of the correspondences used for optimization.
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* \return Transformation from frame 2 back to frame 1 (
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* \f$ \mathbf{T} = \left(\begin{array}{cc} \mathbf{R} & \mathbf{t} \end{array}\right) \f$,
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* with \f$ \mathbf{t} \f$ being the position of frame 2 seen from
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* frame 1, and \f$ \mathbf{R} \f$ being the rotation from
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* frame 2 to frame 1).
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*/
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transformation_t optimize_nonlinear(
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PointCloudAdapterBase & adapter,
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const std::vector<int> & indices );
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}
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}
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#endif /* OPENGV_POINT_CLOUD_METHODS_HPP_ */
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