Deterministic Approximate Methods for Maximum Consensus Robust Fitting

Maximum consensus estimation plays a critically important role in several robust fitting problems in computer vision. Currently, the most prevalent algorithms for consensus maximization draw from the class of randomized hypothesize-and-verify algorithms, which are cheap but can usually deliver only...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 43; H. 3; S. 842 - 857
Hauptverfasser:	Le, Huu, Chin, Tat-Jun, Eriksson, Anders, Do, Thanh-Toan, Suter, David
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.03.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms approximate algorithm Approximation Approximation algorithms Computational modeling Computer vision Data models deterministic algorithm Estimation Mathematical model Maximization Maximum consensus Optimization robust fitting Robustness
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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