|  | // Ceres Solver - A fast non-linear least squares minimizer | 
|  | // Copyright 2020 Google Inc. All rights reserved. | 
|  | // http://ceres-solver.org/ | 
|  | // | 
|  | // 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: nikolaus@nikolaus-demmel.de (Nikolaus Demmel) | 
|  | // | 
|  | // | 
|  | #ifndef CERES_INTERNAL_AUTODIFF_BENCHMARK_PHOTOMETRIC_ERROR_H_ | 
|  | #define CERES_INTERNAL_AUTODIFF_BENCHMARK_PHOTOMETRIC_ERROR_H_ | 
|  |  | 
|  | #include <Eigen/Dense> | 
|  |  | 
|  | #include "ceres/cubic_interpolation.h" | 
|  |  | 
|  | namespace ceres { | 
|  |  | 
|  | // Photometric residual that computes the intensity difference for a patch | 
|  | // between host and target frame. The point is parameterized with inverse | 
|  | // distance relative to the host frame. The relative pose between host and | 
|  | // target frame is computed from their respective absolute poses. | 
|  | // | 
|  | // The residual is similar to the one defined by Engel et al. [1]. Differences | 
|  | // include: | 
|  | // | 
|  | // 1. Use of a camera model based on spherical projection, namely the enhanced | 
|  | // unified camera model [2][3]. This is intended to bring some variability to | 
|  | // the benchmark compared to the SnavelyReprojection that uses a | 
|  | // polynomial-based distortion model. | 
|  | // | 
|  | // 2. To match the camera model, inverse distance parameterization is used for | 
|  | // points instead of inverse depth [4]. | 
|  | // | 
|  | // 3. For simplicity, camera intrinsics are assumed constant, and thus host | 
|  | // frame points are passed as (unprojected) bearing vectors, which avoids the | 
|  | // need for an 'unproject' function. | 
|  | // | 
|  | // 4. Some details of the residual in [1] are omitted for simplicity: The | 
|  | // brightness transform parameters [a,b], the constant pre-weight w, and the | 
|  | // per-pixel robust norm. | 
|  | // | 
|  | // [1] J. Engel, V. Koltun and D. Cremers, "Direct Sparse Odometry," in IEEE | 
|  | // Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 3, | 
|  | // pp. 611-625, 1 March 2018. | 
|  | // | 
|  | // [2] B. Khomutenko, G. Garcia and P. Martinet, "An Enhanced Unified Camera | 
|  | // Model," in IEEE Robotics and Automation Letters, vol. 1, no. 1, pp. 137-144, | 
|  | // Jan. 2016. | 
|  | // | 
|  | // [3] V. Usenko, N. Demmel and D. Cremers, "The Double Sphere Camera Model," | 
|  | // 2018 International Conference on 3D Vision (3DV), Verona, 2018, pp. 552-560. | 
|  | // | 
|  | // [4] H. Matsuki, L. von Stumberg, V. Usenko, J. Stückler and D. Cremers, | 
|  | // "Omnidirectional DSO: Direct Sparse Odometry With Fisheye Cameras," in IEEE | 
|  | // Robotics and Automation Letters, vol. 3, no. 4, pp. 3693-3700, Oct. 2018. | 
|  | template <int PATCH_SIZE_ = 8> | 
|  | struct PhotometricError { | 
|  | static constexpr int PATCH_SIZE = PATCH_SIZE_; | 
|  | static constexpr int POSE_SIZE = 7; | 
|  | static constexpr int POINT_SIZE = 1; | 
|  |  | 
|  | using Grid = Grid2D<uint8_t, 1>; | 
|  | using Interpolator = BiCubicInterpolator<Grid>; | 
|  | using Intrinsics = Eigen::Array<double, 6, 1>; | 
|  |  | 
|  | template <typename T> | 
|  | using Patch = Eigen::Array<T, PATCH_SIZE, 1>; | 
|  |  | 
|  | template <typename T> | 
|  | using PatchVectors = Eigen::Matrix<T, 3, PATCH_SIZE>; | 
|  |  | 
|  | PhotometricError(const Patch<double>& intensities_host, | 
|  | const PatchVectors<double>& bearings_host, | 
|  | const Interpolator& image_target, | 
|  | const Intrinsics& intrinsics) | 
|  | : intensities_host_(intensities_host), | 
|  | bearings_host_(bearings_host), | 
|  | image_target_(image_target), | 
|  | intrinsics_(intrinsics) {} | 
|  |  | 
|  | template <typename T> | 
|  | inline bool Project(Eigen::Matrix<T, 2, 1>& proj, | 
|  | const Eigen::Matrix<T, 3, 1>& p) const { | 
|  | const double& fx = intrinsics_[0]; | 
|  | const double& fy = intrinsics_[1]; | 
|  | const double& cx = intrinsics_[2]; | 
|  | const double& cy = intrinsics_[3]; | 
|  | const double& alpha = intrinsics_[4]; | 
|  | const double& beta = intrinsics_[5]; | 
|  |  | 
|  | const T rho2 = beta * (p.x() * p.x() + p.y() * p.y()) + p.z() * p.z(); | 
|  | const T rho = sqrt(rho2); | 
|  |  | 
|  | // Check if 3D point is in domain of projection function. | 
|  | // See (8) and (17) in [3]. | 
|  | constexpr double NUMERIC_EPSILON = 1e-10; | 
|  | const double w = | 
|  | alpha > 0.5 ? (1.0 - alpha) / alpha : alpha / (1.0 - alpha); | 
|  | if (p.z() <= -w * rho + NUMERIC_EPSILON) { | 
|  | return false; | 
|  | } | 
|  |  | 
|  | const T norm = alpha * rho + (1.0 - alpha) * p.z(); | 
|  | const T norm_inv = 1.0 / norm; | 
|  |  | 
|  | const T mx = p.x() * norm_inv; | 
|  | const T my = p.y() * norm_inv; | 
|  |  | 
|  | proj[0] = fx * mx + cx; | 
|  | proj[1] = fy * my + cy; | 
|  |  | 
|  | return true; | 
|  | } | 
|  |  | 
|  | template <typename T> | 
|  | inline bool operator()(const T* const pose_host_ptr, | 
|  | const T* const pose_target_ptr, | 
|  | const T* const idist_ptr, | 
|  | T* residuals_ptr) const { | 
|  | Eigen::Map<const Eigen::Quaternion<T>> q_w_h(pose_host_ptr); | 
|  | Eigen::Map<const Eigen::Matrix<T, 3, 1>> t_w_h(pose_host_ptr + 4); | 
|  | Eigen::Map<const Eigen::Quaternion<T>> q_w_t(pose_target_ptr); | 
|  | Eigen::Map<const Eigen::Matrix<T, 3, 1>> t_w_t(pose_target_ptr + 4); | 
|  | const T& idist = *idist_ptr; | 
|  | Eigen::Map<Patch<T>> residuals(residuals_ptr); | 
|  |  | 
|  | // Compute relative pose from host to target frame. | 
|  | const Eigen::Quaternion<T> q_t_h = q_w_t.conjugate() * q_w_h; | 
|  | const Eigen::Matrix<T, 3, 3> R_t_h = q_t_h.toRotationMatrix(); | 
|  | const Eigen::Matrix<T, 3, 1> t_t_h = q_w_t.conjugate() * (t_w_h - t_w_t); | 
|  |  | 
|  | // Transform points from host to target frame. 3D point in target frame is | 
|  | // scaled by idist for numerical stability when idist is close to 0 | 
|  | // (projection is invariant to scaling). | 
|  | PatchVectors<T> p_target_scaled = | 
|  | (R_t_h * bearings_host_).colwise() + idist * t_t_h; | 
|  |  | 
|  | // Project points and interpolate image. | 
|  | Patch<T> intensities_target; | 
|  | for (int i = 0; i < p_target_scaled.cols(); ++i) { | 
|  | Eigen::Matrix<T, 2, 1> uv; | 
|  | if (!Project(uv, Eigen::Matrix<T, 3, 1>(p_target_scaled.col(i)))) { | 
|  | // If any point of the patch is outside the domain of the projection | 
|  | // function, the residual cannot be evaluated. For the benchmark we want | 
|  | // to avoid this case and thus return false; | 
|  | return false; | 
|  | } | 
|  |  | 
|  | // Mind the order of u and v: Evaluate takes (row, column), but u is | 
|  | // left-to-right and v top-to-bottom image axis. | 
|  | image_target_.Evaluate(uv[1], uv[0], &intensities_target[i]); | 
|  | } | 
|  |  | 
|  | // Residual is intensity difference between host and target frame. | 
|  | residuals = intensities_target - intensities_host_; | 
|  |  | 
|  | return true; | 
|  | } | 
|  |  | 
|  | private: | 
|  | const Patch<double>& intensities_host_; | 
|  | const PatchVectors<double>& bearings_host_; | 
|  | const Interpolator& image_target_; | 
|  | const Intrinsics& intrinsics_; | 
|  | }; | 
|  | }  // namespace ceres | 
|  | #endif  // CERES_INTERNAL_AUTODIFF_BENCHMARK_PHOTOMETRIC_ERROR_H_ |