Faster octree nearestKSearch#6037
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mvieth merged 1 commit intoPointCloudLibrary:masterfrom May 13, 2024
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Inspired by the logic in organized.h: always keep `point_candidates` sorted, inserting new entries at the correct places. This avoids repeated calls to std::sort and having more than `k` entries in `point_candidates`. Benchmarks: NormalEstimation with octree: | NormalEstimation | Old | New | |-------------------|-----------|------------| | k=50, cloud=milk | 2607 ms | 1842 ms | | k=50, cloud=mug | 2043 ms | 1505 ms | | k=100, cloud=milk | 5650 ms | 3075 ms | | k=100, cloud=mug | 3824 ms | 2436 ms | Calling nearestKSearch on every (valid) point of a cloud: | Search | Old | New | |--------------|-----------|------------| | k=1, cloud1 | 818 ms | 509 ms | | k=1, cloud2 | 791 ms | 613 ms | | k=1, cloud3 | 773 ms | 744 ms | | k=5, cloud1 | 914 ms | 637 ms | | k=5, cloud2 | 950 ms | 780 ms | | k=5, cloud3 | 1083 ms | 1033 ms |
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larshg
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May 13, 2024
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Nice improvements! |
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Inspired by the logic in organized.h: always keep
point_candidatessorted, inserting new entries at the correct places. This avoids repeated calls to std::sort and having more thankentries inpoint_candidates.Benchmarks:
NormalEstimation (without OpenMP) with octree:
Calling nearestKSearch on every (valid) point of a cloud: