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IEEE Transactions on Pattern Analysis and Machine Intelligence / Apr 2021

Graph-Cut RANSAC: Local optimization on spatially coherent structures

Széchenyi Plusz RRF

A new local optimization (LO) technique, called Graph-Cut RANSAC, is proposed for RANSAC-like robust geometric model estimation. To select potential inliers, the proposed LO step applies the graph-cut algorithm, minimizing a labeling energy functional whenever a new so-far-the-best model is found. The energy originates from both the point-to-model residuals and the spatial coherence of the points. The proposed LO step is conceptually simple, easy to implement, globally optimal and efficient. Graph-Cut RANSAC is combined with the bells and whistles of USAC. It has been tested on a number of publicly available datasets on a range of problems - homography, fundamental and essential matrix estimation. It is more geometrically accurate than state-of-the-art methods and runs faster or with similar speed to less accurate alternatives.

Url
DOI: 10.1109/TPAMI.2021.3071812
Authors
Baráth, D.
Matas, Jiri

Kapcsolat

Prof. Dr. Péter Gáspár

Hungary, H-1111 Budapest,
Kende u. 13-17.
+36 1 279 6000
autonom@nemzetilabor.hu

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