Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments
This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algo...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
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MDPI AG
2010-09-01
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Series: | Sensors |
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Online Access: | http://www.mdpi.com/1424-8220/10/10/8865/ |
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author | Álvaro Marcos José M. Cañas Cristina Losada Daniel Pizarro Manuel Mazo Miguel A. Sotelo Juan C. García Marta Marrón-Romera |
author_facet | Álvaro Marcos José M. Cañas Cristina Losada Daniel Pizarro Manuel Mazo Miguel A. Sotelo Juan C. García Marta Marrón-Romera |
author_sort | Álvaro Marcos |
collection | DOAJ |
description | This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found. |
first_indexed | 2024-04-11T22:22:41Z |
format | Article |
id | doaj.art-353e86e0d80345ac911eaef1184b2350 |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-04-11T22:22:41Z |
publishDate | 2010-09-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-353e86e0d80345ac911eaef1184b23502022-12-22T04:00:00ZengMDPI AGSensors1424-82202010-09-0110108865888710.3390/s101008865Stereo Vision Tracking of Multiple Objects in Complex Indoor EnvironmentsÁlvaro MarcosJosé M. CañasCristina LosadaDaniel PizarroManuel MazoMiguel A. SoteloJuan C. GarcíaMarta Marrón-RomeraThis paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.http://www.mdpi.com/1424-8220/10/10/8865/3D trackingBayesian estimationstereo vision sensormobile robots |
spellingShingle | Álvaro Marcos José M. Cañas Cristina Losada Daniel Pizarro Manuel Mazo Miguel A. Sotelo Juan C. García Marta Marrón-Romera Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments Sensors 3D tracking Bayesian estimation stereo vision sensor mobile robots |
title | Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments |
title_full | Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments |
title_fullStr | Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments |
title_full_unstemmed | Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments |
title_short | Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments |
title_sort | stereo vision tracking of multiple objects in complex indoor environments |
topic | 3D tracking Bayesian estimation stereo vision sensor mobile robots |
url | http://www.mdpi.com/1424-8220/10/10/8865/ |
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