Fix #7449: sample_points_poisson_disk is extremely slow by nikste · Pull Request #7450 · isl-org/Open3D

nikste · 2026-03-01T00:50:08Z

Hi all,
I'm trying out some fun project for claude code github issue solver.
I think this should solve the issue. I'm looking at this also as a human.
Let me know if there is something i should change or try.

Summary

Automated fix for #7449: sample_points_poisson_disk is extremely slow

Fixes #7449

What does this PR do?

This PR addresses issue #7449 by implementing the fix described in the issue.

This PR was automatically created by Klaus Kode — donate your excess Claude Code credits to solve open-source issues.

Klaus Kode is not affiliated with or endorsed by Claude Code / Anthropic.

Complaints, praise, or opt-out requests: klauskode@protonmail.com

Replace the O(N × neighbors) weight recomputation in the sample elimination loop with an O(N) incremental update that matches the original paper (Fig. 2) and reference implementation. Previously, when a point was eliminated, `ComputePointWeight` was called for every neighboring point, each of which triggered a new full KD-tree radius search. Now we reuse the distances already returned by the single KD-tree query for the eliminated point and simply subtract its weight contribution from each live neighbor, reducing KD-tree queries during elimination from O(N × avg_neighbors) to O(N) and achieving ~6-10× speedup. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

update-docs · 2026-03-01T00:50:12Z

Thanks for submitting this pull request! The maintainers of this repository would appreciate if you could update the CHANGELOG.md based on your changes.

nikste · 2026-03-01T01:12:12Z

it seems when i run the stylecheck python util/check_style.py --apply as suggeste din the failing test github action, it changes some unrelated files ?

BG4444 · 2026-03-01T16:22:35Z

It still has some performance issues—for example, extra memory allocations for each KD-tree request (new std::vector for each time), and extra weight computations for points that have already been deleted.

nikste · 2026-03-01T17:41:20Z

just benchmarked with the bunny example you gave. The base speedup is already there from ~2.04s down to 0.368s on my machine.
I'll check the further examples you mentioned.

nikste · 2026-03-01T17:53:57Z

I'm moving the vector instantiations to outside of the loop.
It seems the KD lookup is a bit more complex and would have negligible gain for most cases.
"The deleted[nb] check is just a boolean array lookup — extremely cheap (L1 cache hit). Even if 50% of points are deleted, you're just doing a few extra branch-not-taken iterations per query"

Since there is already quite some substantial speedup, I'd defer this to another PR, since we'd either need to periodically recompute the KD tree it seems or expose it through the wrapper of open3d of Flann.

BG4444 · 2026-03-01T19:49:16Z

You might also consider disabling sorting in the KD-tree query output, or leveraging the sorted distances to skip weight computation for small values. The algorithm assumes that below a certain threshold distance, the weight is constant.

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Pull request overview

This PR targets Open3D issue #7449 by improving the performance of TriangleMesh::SamplePointsPoissonDisk through an incremental neighbor-weight update strategy during sample elimination (reducing repeated KD-tree queries).

Changes:

Update Poisson-disk sample elimination to decrement neighbor weights based on the deleted sample’s contribution rather than recomputing weights via additional KD-tree queries.
Add a changelog entry documenting the performance fix for TriangleMesh::SamplePointsPoissonDisk.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

File	Description
`cpp/open3d/geometry/TriangleMesh.cpp`	Optimizes Poisson-disk sampling by updating neighbor weights incrementally after deletions.
`CHANGELOG.md`	Documents the Poisson-disk sampling performance improvement (issue #7449).

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cpp/open3d/geometry/TriangleMesh.cpp

nikste · 2026-03-05T21:10:09Z

Added optional parameter to KD tree search for unsorted results
unit tests
also pulled out the vector instantiations out of the loop.

Let me know if there should be any more changes before merging.

KD tree sorted=true │ 0.347s │ 16384 points
KD tree sorted=false │ 0.309s │ 16384 points
speedup ~11%

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Pull request overview

Copilot reviewed 5 out of 5 changed files in this pull request and generated 3 comments.

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Copilot · 2026-03-06T22:11:33Z

cpp/open3d/geometry/KDTreeFlann.h

+                     std::vector<double> &distance2,
+                     bool sorted = true) const;

    template <typename T>


KDTreeFlann::SearchRadius’s signature was changed by adding a new parameter. Even with a default value, this is an ABI-breaking change (different mangled symbol) for any downstream C++ code built against the previous Open3D library. To avoid breaking existing binaries, consider keeping the original 4-arg overload and adding a new 5-arg overload that forwards internally (and explicitly instantiate both overloads as needed).

Suggested change

template <typename T>

template <typename T>

int SearchRadius(const T &query,

double radius,

std::vector<int> &indices,

std::vector<double> &distance2) const {

return SearchRadius(query, radius, indices, distance2, true);

}

template <typename T>

Copilot · 2026-03-06T22:11:33Z

cpp/tests/geometry/TriangleMesh.cpp

+    double min_dist = std::numeric_limits<double>::max();
+    for (size_t i = 0; i < pcd->points_.size(); ++i) {
+        for (size_t j = i + 1; j < pcd->points_.size(); ++j) {
+            double d = (pcd->points_[i] - pcd->points_[j]).norm();
+            min_dist = std::min(min_dist, d);


This test uses std::numeric_limits and std::min, but this file does not include the standard headers that define them. Please add the appropriate includes (e.g., <limits> and <algorithm>) to avoid relying on transitive includes that may change across platforms/compilers.

Copilot · 2026-03-06T22:11:34Z

cpp/tests/geometry/TriangleMesh.cpp

+    // For 100 points on a triangle with area 0.5, the theoretical Poisson disk
+    // radius is r = 2*sqrt(area/n / (2*sqrt(3))) ≈ 0.057. After sample
+    // elimination the actual minimum distance should be a meaningful fraction
+    // of that. We just check it's not degenerate (> 0.01).
+    EXPECT_GT(min_dist, 0.01);


SamplePointsPoissonDisk relies on RNG-based sampling; this test doesn’t set a fixed seed, and the hard min_dist > 0.01 threshold may vary with randomness/implementation details, risking flaky CI. Consider seeding (e.g., utility::random::Seed(0)) and/or making the assertion deterministic (e.g., only require min_dist to be above a tiny epsilon, or compare against an expected value with a fixed seed).

Suggested change

// For 100 points on a triangle with area 0.5, the theoretical Poisson disk

// radius is r = 2*sqrt(area/n / (2*sqrt(3))) ≈ 0.057. After sample

// elimination the actual minimum distance should be a meaningful fraction

// of that. We just check it's not degenerate (> 0.01).

EXPECT_GT(min_dist, 0.01);

// The exact minimum distance depends on RNG and implementation details.

// To avoid flaky tests, only check that points are not degenerate

// (no coincident samples).

EXPECT_GT(min_dist, 1e-8);

Update changelog

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cpp/open3d/geometry/TriangleMesh.cpp Outdated Show resolved Hide resolved

nikste added 2 commits March 5, 2026 19:32

Move vector declaration outside of loop

70044a4

Add unit tests, add optional unsorted parameter to KDtree search

e2433f6

ssheorey requested a review from Copilot March 6, 2026 22:06

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Fix #7449: sample_points_poisson_disk is extremely slow#7450

Fix #7449: sample_points_poisson_disk is extremely slow#7450
nikste wants to merge 4 commits intoisl-org:mainfrom
nikste:fix/issue-7449

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-    template <typename T>
+    template <typename T>
+    int SearchRadius(const T &query,
+                     double radius,
+                     std::vector<int> &indices,
+                     std::vector<double> &distance2) const {
+        return SearchRadius(query, radius, indices, distance2, true);
+    }
+    template <typename T>

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nikste commented Mar 1, 2026

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