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refactor: implement CRTP-based correspondence generation with KNN and brute-force methods
- Create base_correspondence_generator_t using CRTP pattern for static polymorphism - Implement knn_correspondence_generator_t for fast KNN-based matching - Implement brute_force_correspondence_generator_t with parallel computation support - Maintain backward compatibility by aliasing correspondence_generator_t to KNN version - Add convenience functions for both KNN and brute-force correspondence generation - Include comprehensive validation, ratio test, mutual verification, and distance threshold filtering - Update tests and benchmarks to compare both methods - Benchmark results show brute-force parallel is significantly faster for larger datasets: - 100 descriptors: All methods ~150μs - 500 descriptors: Brute-force parallel 4x faster (~1.3ms vs ~5.5ms) - 1000 descriptors: Brute-force parallel 9x faster (~2.3ms vs ~20-22ms) This refactoring provides flexibility to choose between accuracy-focused KNN methods and performance-focused brute-force methods based on application requirements. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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‎benchmark/pcl/correspondence_benc.cpp‎

Lines changed: 39 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -1,8 +1,7 @@
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#include <catch2/catch_all.hpp>
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#include <cpp-toolbox/pcl/correspondence/correspondence_generator.hpp>
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#include <cpp-toolbox/pcl/correspondence/correspondence.hpp>
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#include <cpp-toolbox/pcl/descriptors/fpfh_extractor.hpp>
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#include <cpp-toolbox/pcl/knn/bfknn.hpp>
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#include <cpp-toolbox/pcl/knn/bfknn_parallel.hpp>
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#include <cpp-toolbox/types/point.hpp>
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#include <random>
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#include <chrono>
@@ -91,12 +90,12 @@ TEST_CASE("对应点生成性能 / Correspondence Generation Performance", "[pcl
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src_cloud->points.resize(num_desc * 10);
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dst_cloud->points.resize(num_desc * 10);
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// 暴力搜索 / Brute-force search
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BENCHMARK("暴力KNN / Brute-force KNN")
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// KNN方法 / KNN method
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BENCHMARK("KNN方法 / KNN method")
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{
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using CorrespondenceGen = correspondence_generator_t<T, fpfh_signature_t<T>,
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bfknn_generic_t<fpfh_signature_t<T>,
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FPFHMetric<T>>>;
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using CorrespondenceGen = knn_correspondence_generator_t<T, fpfh_signature_t<T>,
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bfknn_generic_t<fpfh_signature_t<T>,
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FPFHMetric<T>>>;
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CorrespondenceGen corr_gen;
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auto knn = std::make_shared<bfknn_generic_t<fpfh_signature_t<T>, FPFHMetric<T>>>();
@@ -112,8 +111,39 @@ TEST_CASE("对应点生成性能 / Correspondence Generation Performance", "[pcl
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return correspondences.size();
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};
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// 注释掉并行版本，因为它目前只支持点类型 / Comment out parallel version as it only supports point types
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// TODO: 修复 bfknn_parallel 以支持通用元素类型 / Fix bfknn_parallel to support generic element types
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// 暴力搜索方法（串行） / Brute-force method (serial)
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BENCHMARK("暴力搜索（串行） / Brute-force (serial)")
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{
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brute_force_correspondence_generator_t<T, fpfh_signature_t<T>> corr_gen;
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corr_gen.enable_parallel(false);
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corr_gen.set_source(src_cloud, src_descriptors, src_indices);
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corr_gen.set_destination(dst_cloud, dst_descriptors, dst_indices);
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corr_gen.set_ratio(0.8f);
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corr_gen.set_mutual_verification(true);
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std::vector<correspondence_t> correspondences;
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corr_gen.compute(correspondences);
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return correspondences.size();
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};
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// 暴力搜索方法（并行） / Brute-force method (parallel)
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BENCHMARK("暴力搜索（并行） / Brute-force (parallel)")
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{
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brute_force_correspondence_generator_t<T, fpfh_signature_t<T>> corr_gen;
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corr_gen.enable_parallel(true);
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corr_gen.set_source(src_cloud, src_descriptors, src_indices);
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corr_gen.set_destination(dst_cloud, dst_descriptors, dst_indices);
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corr_gen.set_ratio(0.8f);
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corr_gen.set_mutual_verification(true);
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std::vector<correspondence_t> correspondences;
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corr_gen.compute(correspondences);
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return correspondences.size();
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};
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}
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}
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}

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