Effective outlier matches pruning algorithm for rigid pairwise point cloud registration using distance disparity matrix. Article. Sep 2017. Nan Luo · Quan Wang.
Effective outlier matches pruning algorithm for rigid pairwise point cloud registration using distance disparity matrix · Authors · Source Information · Abstract.
They seek correspondences over downsampled superpoints, which are then propagated to dense points. Superpoints are matched based on whether their neighboring ...
Missing: disparity | Show results with:disparity
To realize this, our first contribution is to integrate the scale-invariant constraint with a double-point random sampling framework to achieve the rapid ...
Missing: disparity | Show results with:disparity
Mar 17, 2023 · We study the problem of outlier correspondence pruning for non-rigid point cloud registration. In rigid registration, spatial consistency ...
Missing: disparity | Show results with:disparity
We study the problem of outlier correspondence pruning for non-rigid point cloud registration. In rigid registration, spatial consistency has been a ...
Zeng et al. (2017) proposed a data-driven method 3DMatch. Geometric descriptors of local regions were learned using 3D convolutional neural networks (3DConvNet) ...
Missing: disparity | Show results with:disparity
Then, we propose an 1-point random sample consensus (RANSAC) algorithm to estimate the scale and translation parameters. For the rotation estimation, we ...
Mar 23, 2024 · Therefore, these feature-based methods have difficulties with generalizing onto point clouds that differ substantially from their training data.
[PDF] Robust Point Cloud Registration with Geometry-based Transformation ...
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Results show that our method effectively reduces outliers and performs similarly to ... “A practical maximum clique algorithm for matching with pairwise.