Improve any image feature matcher on large appearance changes using OETR

Improve any image feature matcher on large appearance changes using OETR

Guide Local Feature Matching by Overlap Estimation
arXiv paper abstract https://arxiv.org/abs/2202.09050
arXiv PDF paper https://arxiv.org/pdf/2202.09050.pdf

Local image feature matching under large appearance, viewpoint, and distance changes is challenging yet important.

Conventional methods detect and match tentative local features across the whole images, with heuristic consistency checks to guarantee reliable matches.

… introduce a novel Overlap Estimation method conditioned on image pairs with TRansformer, named OETR, to constrain local feature matching in the commonly visible region.

OETR performs overlap estimation in a two-step process of feature correlation and then overlap regression.

… OETR can be plugged into any existing local feature detection and matching pipeline, to mitigate potential view angle or scale variance.

… boost state-of-the-art local feature matching performance substantially, especially for image pairs with small shared regions. …

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I apply innovative technologies like machine learning, computer vision, and physics to further an organization's goals. Am recognized innovator with 66 patents.