| // 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: |
| // |
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| // 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 |
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| // specific prior written permission. |
| // |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
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| // 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_ |