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Diffstat (limited to 'thirdparty1/linux/include/opencv2/surface_matching/ppf_helpers.hpp')
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diff --git a/thirdparty1/linux/include/opencv2/surface_matching/ppf_helpers.hpp b/thirdparty1/linux/include/opencv2/surface_matching/ppf_helpers.hpp new file mode 100644 index 0000000..6f3cb77 --- /dev/null +++ b/thirdparty1/linux/include/opencv2/surface_matching/ppf_helpers.hpp @@ -0,0 +1,164 @@ +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2014, OpenCV Foundation, all rights reserved. +// Third party copyrights are property of their respective owners. +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// + +/** @file +@author Tolga Birdal <tbirdal AT gmail.com> +*/ + +#ifndef __OPENCV_SURFACE_MATCHING_HELPERS_HPP__ +#define __OPENCV_SURFACE_MATCHING_HELPERS_HPP__ + +#include <opencv2/core.hpp> + +namespace cv +{ +namespace ppf_match_3d +{ + +//! @addtogroup surface_matching +//! @{ + +/** + * @brief Load a PLY file + * @param [in] fileName The PLY model to read + * @param [in] withNormals Flag wheather the input PLY contains normal information, + * and whether it should be loaded or not + * @return Returns the matrix on successfull load + */ +CV_EXPORTS Mat loadPLYSimple(const char* fileName, int withNormals); + +/** + * @brief Write a point cloud to PLY file + * @param [in] PC Input point cloud + * @param [in] fileName The PLY model file to write +*/ +CV_EXPORTS void writePLY(Mat PC, const char* fileName); + +/** +* @brief Used for debbuging pruposes, writes a point cloud to a PLY file with the tip +* of the normal vectors as visible red points +* @param [in] PC Input point cloud +* @param [in] fileName The PLY model file to write +*/ +CV_EXPORTS void writePLYVisibleNormals(Mat PC, const char* fileName); + +Mat samplePCUniform(Mat PC, int sampleStep); +Mat samplePCUniformInd(Mat PC, int sampleStep, std::vector<int>& indices); + +/** + * Sample a point cloud using uniform steps + * @param [in] pc Input point cloud + * @param [in] xrange X components (min and max) of the bounding box of the model + * @param [in] yrange Y components (min and max) of the bounding box of the model + * @param [in] zrange Z components (min and max) of the bounding box of the model + * @param [in] sample_step_relative The point cloud is sampled such that all points + * have a certain minimum distance. This minimum distance is determined relatively using + * the parameter sample_step_relative. + * @param [in] weightByCenter The contribution of the quantized data points can be weighted + * by the distance to the origin. This parameter enables/disables the use of weighting. + * @return Sampled point cloud +*/ +CV_EXPORTS Mat samplePCByQuantization(Mat pc, float xrange[2], float yrange[2], float zrange[2], float sample_step_relative, int weightByCenter=0); + +void computeBboxStd(Mat pc, float xRange[2], float yRange[2], float zRange[2]); + +void* indexPCFlann(Mat pc); +void destroyFlann(void* flannIndex); +void queryPCFlann(void* flannIndex, Mat& pc, Mat& indices, Mat& distances); +void queryPCFlann(void* flannIndex, Mat& pc, Mat& indices, Mat& distances, const int numNeighbors); + +/** + * Mostly for visualization purposes. Normalizes the point cloud in a Hartley-Zissermann + * fashion. In other words, the point cloud is centered, and scaled such that the largest + * distance from the origin is sqrt(2). Finally a rescaling is applied. + * @param [in] pc Input point cloud (CV_32F family). Point clouds with 3 or 6 elements per + * row are expected. + * @param [in] scale The scale after normalization. Default to 1. + * @return Normalized point cloud +*/ +CV_EXPORTS Mat normalize_pc(Mat pc, float scale); + +Mat normalizePCCoeff(Mat pc, float scale, float* Cx, float* Cy, float* Cz, float* MinVal, float* MaxVal); +Mat transPCCoeff(Mat pc, float scale, float Cx, float Cy, float Cz, float MinVal, float MaxVal); + +/** + * Transforms the point cloud with a given a homogeneous 4x4 pose matrix (in double precision) + * @param [in] pc Input point cloud (CV_32F family). Point clouds with 3 or 6 elements per + * row are expected. In the case where the normals are provided, they are also rotated to be + * compatible with the entire transformation + * @param [in] Pose 4x4 pose matrix, but linearized in row-major form. + * @return Transformed point cloud +*/ +CV_EXPORTS Mat transformPCPose(Mat pc, double Pose[16]); + +/** + * Generate a random 4x4 pose matrix + * @param [out] Pose The random pose +*/ +CV_EXPORTS void getRandomPose(double Pose[16]); + +/** + * Adds a uniform noise in the given scale to the input point cloud + * @param [in] pc Input point cloud (CV_32F family). + * @param [in] scale Input scale of the noise. The larger the scale, the more noisy the output +*/ +CV_EXPORTS Mat addNoisePC(Mat pc, double scale); + +/** + * @brief Compute the normals of an arbitrary point cloud + * computeNormalsPC3d uses a plane fitting approach to smoothly compute + * local normals. Normals are obtained through the eigenvector of the covariance + * matrix, corresponding to the smallest eigen value. + * If PCNormals is provided to be an Nx6 matrix, then no new allocation + * is made, instead the existing memory is overwritten. + * @param [in] PC Input point cloud to compute the normals for. + * @param [in] PCNormals Output point cloud + * @param [in] NumNeighbors Number of neighbors to take into account in a local region + * @param [in] FlipViewpoint Should normals be flipped to a viewing direction? + * @param [in] viewpoint + * @return Returns 0 on success + */ +CV_EXPORTS int computeNormalsPC3d(const Mat& PC, Mat& PCNormals, const int NumNeighbors, const bool FlipViewpoint, const double viewpoint[3]); + +//! @} + +} // namespace ppf_match_3d +} // namespace cv + +#endif |