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A Variational Bayesian Algorithm for Probabilistic Affine and Non-rigid Point Cloud Registration
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DOI：10.1016/j.patcog.2026.113645.png)
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Abstract
En 中文
• Affine alignment is reframed as density estimation, using Student’s t to suppress outliers. • Heterogeneous Student’s t mixture with Gamma-Dirichlet priors models inliers, noise, outliers. • We build a complete pipeline unifying SMM affine alignment, HSMM correspondence, and non-rigid inference. • Experiments on six benchmarks show VBReg exceeds iterative and learning methods in robustness.
Keywords:
Affine alignment
Student’s t mixture
Variational Bayesian
Point cloud registration
Non-rigid inference
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