Robust affine point matching via quadratic assignment on Grassmannians

Alexander Kolpakov, Michael Werman

Research output: Contribution to journalArticlepeer-review

Abstract

Robust Affine Matching with Grassmannians (RoAM) is a new algorithm to perform affine registration of point clouds. The algorithm is based on minimizing the Frobenius distance between two elements of the Grassmannian. For this purpose, an indefinite relaxation of the Quadratic Assignment Problem (QAP) is used, and several approaches to affine feature matching are studied and compared. Experiments demonstrate that RoAM is more robust to noise and point discrepancy than previous methods.

Original languageEnglish
Pages (from-to)265-271
Number of pages7
JournalPattern Recognition Letters
Volume186
DOIs
StatePublished - Oct 2024

Keywords

  • Affine correspondence
  • Affine feature matching
  • Grassmann manifold
  • Point cloud registration
  • Quadratic assignment problem (QAP)
  • Shape matching
  • Singular value decomposition (SVD)

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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