Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/9263
Title: Temporal synchronization in mobile sensor networks using image sequence analysis.
Authors: Brito, Darlan Nunes de
Pádua, Flávio Luis Cardeal
Pereira, Guilherme A. S.
Keywords: Mobile sensor networks
Temporal alignment
Visual object tracking
Random sample consensus
Issue Date: 2014
Citation: BRITO, D. N. de; PÁDUA, F. L. C.; PEREIRA, G. A. S. Temporal synchronization in mobile sensor networks using image sequence analysis. Machine Vision and Applications, v. 25, p. 1067-1076, 2014. Disponível em: <https://link.springer.com/article/10.1007/s00138-014-0605-6>. Acesso em: 02 out. 2017.
Abstract: This paper addresses the problem of estimating the temporal synchronization inmobile sensors’ networks, by using image sequence analysis of their corresponding scene dynamics. Unlike existing methods, which are frequently based on adaptations of techniques originally designed for wired networks with static topologies, or even based on solutions specially designed for ad hoc wireless sensor networks, but that have a high energy consumption and a low scalability regarding the number of sensors, this work proposes a novel approach that reduces the problem of synchronizing a general number N of sensors to the robust estimation of a single line in RN+1. This line captures all temporal relations between the sensors and can be computed without any prior knowledge of these relations. It is assumed that (1) the network’s mobile sensors cross the field of view of a stationary calibrated camera that operates with constant frame rate and (2) the sensors trajectories are estimated with a limited error at a constant sampling rate, both in the world coordinate system and in the camera’s image plane. Experimental results with real-world and synthetic scenarios demonstrate that our method can be successfully used to determine the temporal alignment in mobile sensor networks.
URI: http://www.repositorio.ufop.br/handle/123456789/9263
metadata.dc.identifier.uri2: https://link.springer.com/article/10.1007/s00138-014-0605-6
ISSN: 14321769
Appears in Collections:DECSI - Artigos publicados em periódicos

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