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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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 |
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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 |
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