3DCOMET: 3D compression methods test dataset

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Title: 3DCOMET: 3D compression methods test dataset
Authors: Navarrete, Javier | Morell, Vicente | Cazorla, Miguel | Viejo Hernando, Diego | Garcia-Rodriguez, Jose | Orts-Escolano, Sergio
Research Group/s: Robótica y Visión Tridimensional (RoViT) | Informática Industrial y Redes de Computadores
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial | Universidad de Alicante. Departamento de Tecnología Informática y Computación | Universidad de Alicante. Instituto Universitario de Investigación Informática
Keywords: 3D data | Data compression | Dataset
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial | Arquitectura y Tecnología de Computadores
Issue Date: Jan-2016
Publisher: Elsevier
Citation: Robotics and Autonomous Systems. 2016, 75(B): 550-557. doi:10.1016/j.robot.2015.09.028
Abstract: The use of 3D data in mobile robotics applications provides valuable information about the robot’s environment. However usually the huge amount of 3D information is difficult to manage due to the fact that the robot storage system and computing capabilities are insufficient. Therefore, a data compression method is necessary to store and process this information while preserving as much information as possible. A few methods have been proposed to compress 3D information. Nevertheless, there does not exist a consistent public benchmark for comparing the results (compression level, distance reconstructed error, etc.) obtained with different methods. In this paper, we propose a dataset composed of a set of 3D point clouds with different structure and texture variability to evaluate the results obtained from 3D data compression methods. We also provide useful tools for comparing compression methods, using as a baseline the results obtained by existing relevant compression methods.
Sponsor: This work was partially supported by grant DPI2013-40534-R of the Ministerio of Economia y Competitividad of the Spanish Government, supported with Feder funds, and Valencian’s Government project GV/2014/097.
URI: http://hdl.handle.net/10045/51855
ISSN: 0921-8890 (Print) | 1872-793X (Online)
DOI: 10.1016/j.robot.2015.09.028
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2015 Elsevier B.V.
Peer Review: si
Publisher version: http://dx.doi.org/10.1016/j.robot.2015.09.028
Appears in Collections:INV - RoViT - Artículos de Revistas
INV - I2RC - Artículos de Revistas
INV - AIA - Artículos de Revistas

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