// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2012 Google Inc. All rights reserved. // http://code.google.com/p/ceres-solver/ // // 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 Google Inc. 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 THE COPYRIGHT OWNER 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. // // Author: strandmark@google.com (Petter Strandmark) // // Class for loading the data required for descibing a Fields of Experts (FoE) // model. The Fields of Experts regularization consists of terms of the type // // alpha * log(1 + (1/2)*sum(F .* X)^2), // // where F is a d-by-d image patch and alpha is a constant. This is implemented // by a FieldsOfExpertsSum object which represents the dot product between the // image patches and a FieldsOfExpertsLoss which implements the log(1 + (1/2)s) // part. // // [1] S. Roth and M.J. Black. "Fields of Experts." International Journal of // Computer Vision, 82(2):205--229, 2009. #ifndef CERES_EXAMPLES_FIELDS_OF_EXPERTS_H_ #define CERES_EXAMPLES_FIELDS_OF_EXPERTS_H_ #include <iostream> #include <vector> #include "ceres/loss_function.h" #include "ceres/cost_function.h" #include "ceres/sized_cost_function.h" #include "pgm_image.h" namespace ceres { namespace examples { // One sum in the FoE regularizer. This is a dot product between a filter and an // image patch. It simply calculates the dot product between the filter // coefficients given in the constructor and the scalar parameters passed to it. class FieldsOfExpertsCost : public ceres::CostFunction { public: explicit FieldsOfExpertsCost(const std::vector<double>& filter); // The number of scalar parameters passed to Evaluate must equal the number of // filter coefficients passed to the constructor. virtual bool Evaluate(double const* const* parameters, double* residuals, double** jacobians) const; private: const std::vector<double>& filter_; }; // The loss function used to build the correct regularization. See above. // // f(x) = alpha_i * log(1 + (1/2)s) // class FieldsOfExpertsLoss : public ceres::LossFunction { public: explicit FieldsOfExpertsLoss(double alpha) : alpha_(alpha) { } virtual void Evaluate(double, double*) const; private: const double alpha_; }; // This class loads a set of filters and coefficients from file. Then the users // obtains the correct loss and cost functions through NewCostFunction and // NewLossFunction. class FieldsOfExperts { public: // Creates an empty object with size() == 0. FieldsOfExperts(); // Attempts to load filters from a file. If unsuccessful it returns false and // sets size() == 0. bool LoadFromFile(const std::string& filename); // Side length of a square filter in this FoE. They are all of the same size. int Size() const { return size_; } // Total number of pixels the filter covers. int NumVariables() const { return size_ * size_; } // Number of filters used by the FoE. int NumFilters() const { return num_filters_; } // Creates a new cost function. The caller is responsible for deallocating the // memory. alpha_index specifies which filter is used in the cost function. ceres::CostFunction* NewCostFunction(int alpha_index) const; // Creates a new loss function. The caller is responsible for deallocating the // memory. alpha_index specifies which filter this loss function is for. ceres::LossFunction* NewLossFunction(int alpha_index) const; // Gets the delta pixel indices for all pixels in a patch. const std::vector<int>& GetXDeltaIndices() const { return x_delta_indices_; } const std::vector<int>& GetYDeltaIndices() const { return y_delta_indices_; } private: // The side length of a square filter. int size_; // The number of different filters used. int num_filters_; // Pixel offsets for all variables. std::vector<int> x_delta_indices_, y_delta_indices_; // The coefficients in front of each term. std::vector<double> alpha_; // The filters used for the dot product with image patches. std::vector<std::vector<double> > filters_; }; } // namespace examples } // namespace ceres #endif // CERES_EXAMPLES_FIELDS_OF_EXPERTS_H_