static const char *copyright = " Copyright (c) 2013 Laurent Kneip, ANU. All rights reserved."; /****************************************************************************** * Author: Laurent Kneip * * Contact: kneip.laurent@gmail.com * * License: Copyright (c) 2013 Laurent Kneip, ANU. All rights reserved. * * * * Redistribution and use in source and binary forms, with or without * * modification, are permitted provided that the following conditions * * are met: * * * Redistributions of source code must retain the above copyright * * notice, this list of conditions and the following disclaimer. * * * Redistributions 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. * * * Neither the name of ANU nor the names of its contributors may 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 ANU OR THE 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. * ******************************************************************************/ // Matlab usage: // // X = opengv_experimental1( data11, data12, data13, ..., data21, data22, data23, ..., camOffsets, algorithm ) // // where // data1x and data2x are matched points (each one of dimension 3xn) // camOffsets is a 3xn matrix, with being the number of cameras // algorithm is 0 for sixpt, 1 for ge, and 2 for seventeenpt // X is a 3x5 matrix returning the found transformation, plus the number of // Ransac-iterations and inliers // //matlab header //standard headers #include #include #include #include "mex.h" //include generic headers for opengv stuff #include //include the matlab-adapter #include //expose all ransac-facilities to matlab #include #include typedef opengv::sac_problems::relative_pose::MultiNoncentralRelativePoseSacProblem nrelRansac; typedef std::shared_ptr nrelRansacPtr; // The main mex-function void mexFunction( int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[] ) { //no error-checking here yet, simply provide the right input!! //get number of cameras int numberCams = (nrhs-2)/2; const mxArray *camOffsets = prhs[nrhs-2]; const mxArray *temp1 = prhs[nrhs-1]; double *temp2 = (double*) mxGetData(temp1); int algorithm = floor(temp2[0]+0.01); std::vector bearingVectors1; std::vector bearingVectors2; std::vector numberBearingVectors; for( int cam = 0; cam < numberCams; cam++ ) { const mxArray *data1 = prhs[cam]; const mxArray *data2 = prhs[cam+numberCams]; bearingVectors1.push_back((double*) mxGetData(data1)); bearingVectors2.push_back((double*) mxGetData(data2)); const mwSize *dataDim = mxGetDimensions(data1); numberBearingVectors.push_back(dataDim[1]); } opengv::relative_pose::RelativeMultiAdapterBase* relativeAdapter = new opengv::relative_pose::MANoncentralRelativeMulti( bearingVectors1, bearingVectors2, (double*) mxGetData(camOffsets), numberBearingVectors ); nrelRansacPtr problem; switch(algorithm) { case 0: problem = nrelRansacPtr( new nrelRansac( *relativeAdapter, nrelRansac::SIXPT ) ); break; case 1: problem = nrelRansacPtr( new nrelRansac( *relativeAdapter, nrelRansac::GE ) ); break; case 2: problem = nrelRansacPtr( new nrelRansac( *relativeAdapter, nrelRansac::SEVENTEENPT ) ); break; } opengv::sac::MultiRansac ransac; ransac.sac_model_ = problem; ransac.threshold_ = 2.0*(1.0 - cos(atan(sqrt(2.0)*0.5/800.0))); ransac.max_iterations_ = 10000000; ransac.computeModel(); Eigen::Matrix result; result.block<3,4>(0,0) = ransac.model_coefficients_; result(0,4) = ransac.iterations_; result(1,4) = ransac.inliers_.size(); int dims[2]; dims[0] = 3; dims[1] = 5; plhs[0] = mxCreateNumericArray(2, dims, mxDOUBLE_CLASS, mxREAL); memcpy(mxGetData(plhs[0]), result.data(), 15*sizeof(double)); }