Detection and segmentation of 3D objects in urban environments using indexation

Alfonso Ramirez Pedraza, Jose Joel Gonzalez Barbosa, Juan B. Hurtado Ramos, Angel Ivan Garcia Moreno, Francisco Javier Ornelas Rodriguez, Erick Alejandro Gonzalez Barbosa

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

4 Citas (Scopus)

Resumen

A procedure for automobile detection on 3D point clouds of urban areas is presented in this work. Point clouds are obtained using an HDL-64E Velodyne LIDAR. The work is divided into two sections: Segmentation, in which the base plane (floor) and its perpendicular planes are extracted using Hough's technique. Next every other object is segmented using MeanShift method; and Indexation, in which all segmented objects are modeled according to a normal direction so that its histograms can be obtained and compared to a pre-loaded histogram database. The reconstructed environment is considered to be semi-structured, meaning that it can be modeled using planes. In the process ROC analysis is used for thresholds optimization.

Idioma originalInglés
Número de artículo7106365
Páginas (desde-hasta)1120-1128
Número de páginas9
PublicaciónIEEE Latin America Transactions
Volumen13
N.º4
DOI
EstadoPublicada - 1 abr. 2015
Publicado de forma externa

Huella

Profundice en los temas de investigación de 'Detection and segmentation of 3D objects in urban environments using indexation'. En conjunto forman una huella única.

Citar esto