Cargando…

Scene Acquisition with Multiple 2D and 3D Optical Sensors: A PSO-Based Visibility Optimization

Designing an acquisition system for 2D or 3D information, based on the integration of data provided by different sensors is a task that requires a labor-intensive initial design phase. Indeed, the definition of the architecture of such acquisition systems needs to start from the identification of th...

Descripción completa

Detalles Bibliográficos
Autores principales: Buonamici, Francesco, Furferi, Rocco, Governi, Lapo, Marzola, Antonio, Volpe, Yary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146605/
https://www.ncbi.nlm.nih.gov/pubmed/32204555
http://dx.doi.org/10.3390/s20061726
_version_ 1783520239675244544
author Buonamici, Francesco
Furferi, Rocco
Governi, Lapo
Marzola, Antonio
Volpe, Yary
author_facet Buonamici, Francesco
Furferi, Rocco
Governi, Lapo
Marzola, Antonio
Volpe, Yary
author_sort Buonamici, Francesco
collection PubMed
description Designing an acquisition system for 2D or 3D information, based on the integration of data provided by different sensors is a task that requires a labor-intensive initial design phase. Indeed, the definition of the architecture of such acquisition systems needs to start from the identification of the position and orientation of the sensors observing the scene. Their placement is carefully studied to enhance the efficacy of the system. This often coincides with the need to maximize the surfaces observed by the sensors or some other metric. An automatic optimization procedure based on the Particle Swarm Optimization (PSO) algorithm, to seek the most convenient setting of multiple optical sensors observing a 3D scene, is proposed. The procedure has been developed to provide a fast and efficient tool for 2D and 3D data acquisition. Three different objective functions of general validity, to be used in future applications, are proposed and described in the text. Various filters are introduced to reduce computational times of the whole procedure. The method is capable of handling occlusions from undesired obstacle in the scene. Finally, the entire method is discussed with reference to 1) the development of a body scanner for the arm-wrist-hand district and 2) the acquisition of an internal environment as case studies.
format Online
Article
Text
id pubmed-7146605
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-71466052020-04-20 Scene Acquisition with Multiple 2D and 3D Optical Sensors: A PSO-Based Visibility Optimization Buonamici, Francesco Furferi, Rocco Governi, Lapo Marzola, Antonio Volpe, Yary Sensors (Basel) Article Designing an acquisition system for 2D or 3D information, based on the integration of data provided by different sensors is a task that requires a labor-intensive initial design phase. Indeed, the definition of the architecture of such acquisition systems needs to start from the identification of the position and orientation of the sensors observing the scene. Their placement is carefully studied to enhance the efficacy of the system. This often coincides with the need to maximize the surfaces observed by the sensors or some other metric. An automatic optimization procedure based on the Particle Swarm Optimization (PSO) algorithm, to seek the most convenient setting of multiple optical sensors observing a 3D scene, is proposed. The procedure has been developed to provide a fast and efficient tool for 2D and 3D data acquisition. Three different objective functions of general validity, to be used in future applications, are proposed and described in the text. Various filters are introduced to reduce computational times of the whole procedure. The method is capable of handling occlusions from undesired obstacle in the scene. Finally, the entire method is discussed with reference to 1) the development of a body scanner for the arm-wrist-hand district and 2) the acquisition of an internal environment as case studies. MDPI 2020-03-19 /pmc/articles/PMC7146605/ /pubmed/32204555 http://dx.doi.org/10.3390/s20061726 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Buonamici, Francesco
Furferi, Rocco
Governi, Lapo
Marzola, Antonio
Volpe, Yary
Scene Acquisition with Multiple 2D and 3D Optical Sensors: A PSO-Based Visibility Optimization
title Scene Acquisition with Multiple 2D and 3D Optical Sensors: A PSO-Based Visibility Optimization
title_full Scene Acquisition with Multiple 2D and 3D Optical Sensors: A PSO-Based Visibility Optimization
title_fullStr Scene Acquisition with Multiple 2D and 3D Optical Sensors: A PSO-Based Visibility Optimization
title_full_unstemmed Scene Acquisition with Multiple 2D and 3D Optical Sensors: A PSO-Based Visibility Optimization
title_short Scene Acquisition with Multiple 2D and 3D Optical Sensors: A PSO-Based Visibility Optimization
title_sort scene acquisition with multiple 2d and 3d optical sensors: a pso-based visibility optimization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146605/
https://www.ncbi.nlm.nih.gov/pubmed/32204555
http://dx.doi.org/10.3390/s20061726
work_keys_str_mv AT buonamicifrancesco sceneacquisitionwithmultiple2dand3dopticalsensorsapsobasedvisibilityoptimization
AT furferirocco sceneacquisitionwithmultiple2dand3dopticalsensorsapsobasedvisibilityoptimization
AT governilapo sceneacquisitionwithmultiple2dand3dopticalsensorsapsobasedvisibilityoptimization
AT marzolaantonio sceneacquisitionwithmultiple2dand3dopticalsensorsapsobasedvisibilityoptimization
AT volpeyary sceneacquisitionwithmultiple2dand3dopticalsensorsapsobasedvisibilityoptimization