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 (, José Joel González Barbosa (, Juan B. Hurtado Ramos (, Ángel Iván García Moreno (, Francisco Javier Ornelas Rodriguez (, Erick Alejandro González Barbosa (


This paper appears in: Revista IEEE América Latina

Publication Date: April 2015
Volume: 13,   Issue: 4 
ISSN: 1548-0992

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.

Index Terms:
Indexation, LIDAR, 3D Segmentation.   

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