<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-01T11:56:00Z</responseDate><request verb="GetRecord" identifier="oai:riuma.uma.es:10630/9616" metadataPrefix="qdc">https://riuma.uma.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:riuma.uma.es:10630/9616</identifier><datestamp>2026-02-03T12:19:55Z</datestamp><setSpec>com_10630_2254</setSpec><setSpec>col_10630_37959</setSpec></header><metadata><qdc:qualifieddc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:qdc="http://dspace.org/qualifieddc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
   <dc:title>3D Segmentation Method for Natural Environments based on a Geometric-Featured Voxel Map</dc:title>
   <dc:creator>Plaza, Victoria</dc:creator>
   <dc:creator>Ababsa, Fakhr-Eddine</dc:creator>
   <dc:creator>García-Cerezo, Alfonso José</dc:creator>
   <dc:creator>Gómez-Ruiz, José Antonio</dc:creator>
   <dc:subject>Ingeniería de sistemas</dc:subject>
   <dcterms:abstract>This work proposes a new segmentation algorithm for three-dimensional dense point clouds and has been&#xd;
specially designed for natural environments where the ground is unstructured and may include big slopes, non-flat areas and&#xd;
isolated areas. This technique is based on a Geometric-Featured Voxel map (GFV) where the scene is discretized in&#xd;
constant size cubes or voxels which are classified in flat surface, linear or tubular structures and scattered or undefined&#xd;
shapes, usually corresponding to vegetation. Since this is not a point-based technique the computational cost is significantly&#xd;
reduced, hence it may be compatible with Real-Time applications. The ground is extracted in order to obtain more accurate&#xd;
results in the posterior segmentation process. The scene is split into objects and a second segmentation in regions inside&#xd;
each object is performed based on the voxel’s geometric class. The work here evaluates the proposed algorithm in various&#xd;
versions and several voxel sizes and compares the results with other methods from the literature. For the segmentation&#xd;
evaluation the algorithms are tested on several differently challenging hand-labeled data sets using two metrics, one of which&#xd;
is novel.</dcterms:abstract>
   <dcterms:dateAccepted>2015-03-26T13:47:04Z</dcterms:dateAccepted>
   <dcterms:available>2015-03-26T13:47:04Z</dcterms:available>
   <dcterms:created>2015-03-26T13:47:04Z</dcterms:created>
   <dcterms:issued>2015-03-26</dcterms:issued>
   <dc:type>conference output</dc:type>
   <dc:identifier>http://hdl.handle.net/10630/9616</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>2015 IEEE Industrial Electronics Society</dc:relation>
   <dc:relation>Sevilla</dc:relation>
   <dc:relation>Marzo 2015</dc:relation>
   <dc:rights>open access</dc:rights>
</qdc:qualifieddc>
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