Detección y Segmentación de Objetos 3D in Áreas Urbanas Utilizando Indexación
(Detection and Segmentation of 3D Objects in Urban Environments Using Indexation)
Alfonso Ramírez Pedraza (firstname.lastname@example.org)1, José Joel González Barbosa (email@example.com)1, Juan B. Hurtado Ramos (firstname.lastname@example.org)1, Ángel Iván García Moreno (email@example.com)1, Francisco Javier Ornelas Rodriguez (firstname.lastname@example.org)1, Erick Alejandro González Barbosa (email@example.com)2
This paper appears in: Revista IEEE América Latina
Publication Date: April 2015
Volume: 13, Issue: 4
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.
Indexation, LIDAR, 3D Segmentation.
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