Hierarchical Representation Via Message Propagation for Robust Model Fitting

In this article, we propose a novel hierarchical representation via message propagation (HRMP) method for robust model fitting, which simultaneously takes advantages of both the consensus analysis and the preference analysis to estimate the parameters of multiple model instances from data corrupted...

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Veröffentlicht in:	IEEE transactions on industrial electronics (1982) 2021-09, Vol.68 (9), p.8582-8592
Hauptverfasser:	Lin, Shuyuan, Wang, Xing, Xiao, Guobao, Yan, Yan, Wang, Hanzi
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Algorithms Analytical models Apexes Clustering algorithms Computational modeling Computer vision Data models Data points hierarchical representation Hypotheses Mathematical models message passing model fitting multistructural data Outliers (statistics) Parameter estimation Preference analysis Propagation Representations Robustness
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