Description

Package: Gaussian Density Model
Type: Package
Title: Clustering via the Gaussian Density Model Algorithm
Version: 1.0
Date: 2019-09-20
Web Page: https://github.com/PARPedraza/GaussianDensityModel
Authors: Alfonso Ramírez-Pedraza, CIO A. C., Loma del Bosque 115, Col. Lomas del Campestre, León, Gto, México, C.P. 37150, <ponchorp.1985@gmail.com> and José-Joel gonzalez-Barbosa, CICATA-IPN, Cerro-Blanco 141, Colinas del Cimatario, Querétaro, Qro. Mexico, C.P. 76090, <jgonzalezba@ipn.mx>
Depends: numpy, pandas
Description: We proposes a novel and robust 3D object segmentation method,  the Gaussian Density Model (GDM) algorithm. The algorithm works with point clouds scanned in the urban environment using the density metrics, based on existing quantity of features in the neighborhood. The LiDAR Velodyne 64E was used to scan urban environment.
NeedsCompilation: test-example
Packaged: 2019-09-20 09:35:42 UTC; Guadalajara, Mexic, Monterrey
Repository: PARPedraza
Date/Publication: 2019-09-20 09:35:42
Cite:
@article{article,
author = {A. R. Pedraza, J. J. G. Barbosa, K. L. F. Rodríguez, A. I. G. Moreno and E. A. G. Barbosa},
year = {2019},
month = {},
pages = {},
title = {Free-form object segmentation in urbanenvironments using Gaussian Density Model},
volume = {},
journal = {Latin America Transactions, IEEE (Revista IEEE America Latina},
doi = {10.1109/TLA.}
}