Quantized Residual Preference Based Linkage Clustering for Model Selection and Inlier Segmentation in Geometric Multi-Model Fitting

In this paper, quantized residual preference is proposed to represent the hypotheses and the points for model selection and inlier segmentation in multi-structure geometric model fitting. First, a quantized residual preference is proposed to represent the hypotheses. Through a weighted similarity me...

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Detalles Bibliográficos
Autores principales: Zhao, Qing, Zhang, Yun, Qin, Qianqing, Luo, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374324/
https://www.ncbi.nlm.nih.gov/pubmed/32646048
http://dx.doi.org/10.3390/s20133806

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374324/
https://www.ncbi.nlm.nih.gov/pubmed/32646048
http://dx.doi.org/10.3390/s20133806

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