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123 lines
5.0 KiB
123 lines
5.0 KiB
/* |
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* Software License Agreement (BSD License) |
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* |
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* Copyright (c) 2009, Willow Garage, Inc. |
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* 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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* |
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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 |
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* copyright notice, this list of conditions and the following |
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* disclaimer in the documentation and/or other materials provided |
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* with the distribution. |
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* * Neither the name of Willow Garage, Inc. nor the names of its |
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* contributors may be used to endorse or promote products derived |
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* from this software without specific prior written permission. |
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* |
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS |
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE |
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, |
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, |
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; |
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* 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 |
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
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* POSSIBILITY OF SUCH DAMAGE. |
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* |
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*/ |
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#ifndef __OPENCV_CONDITIONING_HPP__ |
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#define __OPENCV_CONDITIONING_HPP__ |
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#include <opencv2/core.hpp> |
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namespace cv |
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{ |
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namespace sfm |
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{ |
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//! @addtogroup conditioning |
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//! @{ |
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/** Point conditioning (non isotropic). |
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@param points Input vector of N-dimensional points. |
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@param T Output 3x3 transformation matrix. |
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Computes the transformation matrix such that the two principal moments of the set of points are equal to unity, |
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forming an approximately symmetric circular cloud of points of radius 1 about the origin.\n |
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Reference: @cite HartleyZ00 4.4.4 pag.109 |
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*/ |
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CV_EXPORTS_W |
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void |
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preconditionerFromPoints( InputArray points, |
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OutputArray T ); |
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/** @brief Point conditioning (isotropic). |
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@param points Input vector of N-dimensional points. |
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@param T Output 3x3 transformation matrix. |
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Computes the transformation matrix such that each coordinate direction will be scaled equally, |
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bringing the centroid to the origin with an average centroid \f$(1,1,1)^T\f$.\n |
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Reference: @cite HartleyZ00 4.4.4 pag.107. |
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*/ |
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CV_EXPORTS_W |
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void |
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isotropicPreconditionerFromPoints( InputArray points, |
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OutputArray T ); |
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/** @brief Apply Transformation to points. |
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@param points Input vector of N-dimensional points. |
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@param T Input 3x3 transformation matrix such that \f$x = T*X\f$, where \f$X\f$ are the points to transform and \f$x\f$ the transformed points. |
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@param transformed_points Output vector of N-dimensional transformed points. |
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*/ |
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CV_EXPORTS_W |
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void |
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applyTransformationToPoints( InputArray points, |
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InputArray T, |
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OutputArray transformed_points ); |
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/** @brief This function normalizes points (non isotropic). |
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@param points Input vector of N-dimensional points. |
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@param normalized_points Output vector of the same N-dimensional points but with mean 0 and average norm \f$\sqrt{2}\f$. |
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@param T Output 3x3 transform matrix such that \f$x = T*X\f$, where \f$X\f$ are the points to normalize and \f$x\f$ the normalized points. |
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Internally calls @ref preconditionerFromPoints in order to get the scaling matrix before applying @ref applyTransformationToPoints. |
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This operation is an essential step before applying the DLT algorithm in order to consider the result as optimal.\n |
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Reference: @cite HartleyZ00 4.4.4 pag.109 |
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*/ |
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CV_EXPORTS_W |
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void |
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normalizePoints( InputArray points, |
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OutputArray normalized_points, |
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OutputArray T ); |
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/** @brief This function normalizes points. (isotropic). |
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@param points Input vector of N-dimensional points. |
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@param normalized_points Output vector of the same N-dimensional points but with mean 0 and average norm \f$\sqrt{2}\f$. |
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@param T Output 3x3 transform matrix such that \f$x = T*X\f$, where \f$X\f$ are the points to normalize and \f$x\f$ the normalized points. |
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Internally calls @ref preconditionerFromPoints in order to get the scaling matrix before applying @ref applyTransformationToPoints. |
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This operation is an essential step before applying the DLT algorithm in order to consider the result as optimal.\n |
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Reference: @cite HartleyZ00 4.4.4 pag.107. |
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*/ |
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CV_EXPORTS_W |
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void |
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normalizeIsotropicPoints( InputArray points, |
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OutputArray normalized_points, |
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OutputArray T ); |
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//! @} sfm |
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} /* namespace sfm */ |
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} /* namespace cv */ |
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#endif |
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/* End of file. */ |