Drop triangulation pairs with double associations.
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@ -4,6 +4,7 @@
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#include <iomanip>
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#include <iomanip>
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#include <map>
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#include <map>
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#include <numeric>
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#include <numeric>
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#include <set>
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#include <unordered_map>
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#include <unordered_map>
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#include "camera.hpp"
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#include "camera.hpp"
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@ -803,8 +804,106 @@ std::vector<std::vector<std::array<float, 4>>> TriangulatorInternal::triangulate
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groups = calc_grouping(all_pairs, all_scored_poses, min_match_score);
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groups = calc_grouping(all_pairs, all_scored_poses, min_match_score);
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// Drop groups with too few matches
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// Drop groups with too few matches
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size_t num_groups = groups.size();
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size_t num_groups_1 = groups.size();
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for (size_t i = num_groups; i > 0; --i)
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for (size_t i = num_groups_1; i > 0; --i)
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{
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if (std::get<2>(groups[i - 1]).size() < this->min_group_size)
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{
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groups.erase(groups.begin() + i - 1);
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}
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}
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// Drop pairs with double associations, where the same 2D person appears in multiple pairs.
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// If two not-same persons have relatively similar poses, the triangulation could create a
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// false positive virtual person. This can lead to a single 2D skeleton being associated with
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// multiple 3D skeletons. To avoid this, check if the same 2D person appears in multiple valid
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// pairs. If so, drop the pairs in less populated groups or with the lower scores.
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std::map<std::tuple<int, int, int>, std::vector<size_t>> pairs_map;
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for (size_t i = 0; i < all_pairs.size(); ++i)
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{
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const auto &p = all_pairs[i];
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const auto &mid1 = std::make_tuple(
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std::get<0>(p.first), std::get<1>(p.first), std::get<0>(p.second));
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const auto &mid2 = std::make_tuple(
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std::get<0>(p.first), std::get<1>(p.first), std::get<1>(p.second));
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pairs_map[mid1].push_back(i);
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pairs_map[mid2].push_back(i);
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}
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std::vector<size_t> group_map;
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group_map.resize(all_pairs.size());
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for (size_t i = 0; i < groups.size(); ++i)
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{
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const auto &group = groups[i];
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const auto &indices = std::get<2>(group);
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for (const auto &idx : indices)
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{
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group_map[idx] = i;
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}
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}
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std::set<size_t> drop_indices;
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for (auto &pair : pairs_map)
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{
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auto &indices = pair.second;
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if (indices.size() > 1)
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{
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std::vector<size_t> group_sizes;
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std::vector<float> pair_scores;
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for (auto &idx : indices)
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{
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group_sizes.push_back(std::get<2>(groups[group_map[idx]]).size());
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pair_scores.push_back(all_scored_poses[idx].second);
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}
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// Sort indices by group size (prio-1) and pair score (prio-2)
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std::vector<size_t> indices_sorted(indices.size());
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std::iota(indices_sorted.begin(), indices_sorted.end(), 0);
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std::sort(indices_sorted.begin(), indices_sorted.end(),
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[&group_sizes, &pair_scores](size_t a, size_t b)
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{
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if (group_sizes[a] != group_sizes[b])
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{
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return group_sizes[a] > group_sizes[b];
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}
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return pair_scores[a] > pair_scores[b];
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});
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// Drop all but the first index
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for (size_t j = 1; j < indices_sorted.size(); ++j)
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{
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size_t drop_idx = indices[indices_sorted[j]];
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drop_indices.insert(drop_idx);
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}
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}
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}
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std::vector<size_t> drop_list(drop_indices.begin(), drop_indices.end());
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std::sort(drop_list.begin(), drop_list.end(), std::greater<size_t>());
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for (size_t i = 0; i < drop_list.size(); ++i)
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{
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all_scored_poses.erase(all_scored_poses.begin() + drop_list[i]);
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all_pairs.erase(all_pairs.begin() + drop_list[i]);
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// Remove pairs from groups and update indices of the remaining pairs
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for (size_t j = 0; j < groups.size(); ++j)
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{
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auto &indices = std::get<2>(groups[j]);
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auto it = std::find(indices.begin(), indices.end(), drop_list[i]);
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if (it != indices.end())
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{
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indices.erase(it);
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}
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for (size_t k = 0; k < std::get<2>(groups[j]).size(); ++k)
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{
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if ((size_t)std::get<2>(groups[j])[k] > drop_list[i])
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{
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std::get<2>(groups[j])[k] -= 1;
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}
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}
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}
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}
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// Drop groups with too few matches again
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size_t num_groups_2 = groups.size();
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for (size_t i = num_groups_2; i > 0; --i)
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{
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{
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if (std::get<2>(groups[i - 1]).size() < this->min_group_size)
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if (std::get<2>(groups[i - 1]).size() < this->min_group_size)
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{
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{
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