| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2022 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: kushalav@google.com (Avanish Kushal) |
| |
| #include "ceres/visibility.h" |
| |
| #include <algorithm> |
| #include <cmath> |
| #include <ctime> |
| #include <memory> |
| #include <set> |
| #include <unordered_map> |
| #include <utility> |
| #include <vector> |
| |
| #include "ceres/block_structure.h" |
| #include "ceres/graph.h" |
| #include "ceres/pair_hash.h" |
| #include "glog/logging.h" |
| |
| namespace ceres::internal { |
| |
| void ComputeVisibility(const CompressedRowBlockStructure& block_structure, |
| const int num_eliminate_blocks, |
| std::vector<std::set<int>>* visibility) { |
| CHECK(visibility != nullptr); |
| |
| // Clear the visibility vector and resize it to hold a |
| // vector for each camera. |
| visibility->resize(0); |
| visibility->resize(block_structure.cols.size() - num_eliminate_blocks); |
| |
| for (const auto& row : block_structure.rows) { |
| const std::vector<Cell>& cells = row.cells; |
| int block_id = cells[0].block_id; |
| // If the first block is not an e_block, then skip this row block. |
| if (block_id >= num_eliminate_blocks) { |
| continue; |
| } |
| |
| for (int j = 1; j < cells.size(); ++j) { |
| int camera_block_id = cells[j].block_id - num_eliminate_blocks; |
| DCHECK_GE(camera_block_id, 0); |
| DCHECK_LT(camera_block_id, visibility->size()); |
| (*visibility)[camera_block_id].insert(block_id); |
| } |
| } |
| } |
| |
| std::unique_ptr<WeightedGraph<int>> CreateSchurComplementGraph( |
| const std::vector<std::set<int>>& visibility) { |
| const time_t start_time = time(nullptr); |
| // Compute the number of e_blocks/point blocks. Since the visibility |
| // set for each e_block/camera contains the set of e_blocks/points |
| // visible to it, we find the maximum across all visibility sets. |
| int num_points = 0; |
| for (const auto& visible : visibility) { |
| if (!visible.empty()) { |
| num_points = std::max(num_points, (*visible.rbegin()) + 1); |
| } |
| } |
| |
| // Invert the visibility. The input is a camera->point mapping, |
| // which tells us which points are visible in which |
| // cameras. However, to compute the sparsity structure of the Schur |
| // Complement efficiently, its better to have the point->camera |
| // mapping. |
| std::vector<std::set<int>> inverse_visibility(num_points); |
| for (int i = 0; i < visibility.size(); i++) { |
| const std::set<int>& visibility_set = visibility[i]; |
| for (int v : visibility_set) { |
| inverse_visibility[v].insert(i); |
| } |
| } |
| |
| // Map from camera pairs to number of points visible to both cameras |
| // in the pair. |
| std::unordered_map<std::pair<int, int>, int, pair_hash> camera_pairs; |
| |
| // Count the number of points visible to each camera/f_block pair. |
| for (const auto& inverse_visibility_set : inverse_visibility) { |
| for (auto camera1 = inverse_visibility_set.begin(); |
| camera1 != inverse_visibility_set.end(); |
| ++camera1) { |
| auto camera2 = camera1; |
| for (++camera2; camera2 != inverse_visibility_set.end(); ++camera2) { |
| ++(camera_pairs[std::make_pair(*camera1, *camera2)]); |
| } |
| } |
| } |
| |
| auto graph = std::make_unique<WeightedGraph<int>>(); |
| |
| // Add vertices and initialize the pairs for self edges so that self |
| // edges are guaranteed. This is needed for the Canonical views |
| // algorithm to work correctly. |
| static constexpr double kSelfEdgeWeight = 1.0; |
| for (int i = 0; i < visibility.size(); ++i) { |
| graph->AddVertex(i); |
| graph->AddEdge(i, i, kSelfEdgeWeight); |
| } |
| |
| // Add an edge for each camera pair. |
| for (const auto& camera_pair_count : camera_pairs) { |
| const int camera1 = camera_pair_count.first.first; |
| const int camera2 = camera_pair_count.first.second; |
| const int count = camera_pair_count.second; |
| DCHECK_NE(camera1, camera2); |
| // Static cast necessary for Windows. |
| const double weight = |
| static_cast<double>(count) / |
| (sqrt(static_cast<double>(visibility[camera1].size() * |
| visibility[camera2].size()))); |
| graph->AddEdge(camera1, camera2, weight); |
| } |
| |
| VLOG(2) << "Schur complement graph time: " << (time(nullptr) - start_time); |
| return graph; |
| } |
| |
| } // namespace ceres::internal |