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Gap Filling of Missing Streaming Data in a Network of Intelligent Surveillance Cameras

Published: 17 October 2017 Publication History

Abstract

The growth of video surveillance devices increases the rate of streaming data. However, even working in the Fog Computing environment, these smart devices may fail collecting information, producing missing or invalid data. This issue can affect the user quality of experience, because the PTZ-controller may lose the target object tracking. Therefore, this paper presents the Singular Spectrum Analysis - (SSA), as the method to replace missing values in this complex environment of intelligent surveillance cameras. SSA is characterized within time series field by performing a non-parametric spectral estimation with spatial-temporal correlations. The values not correctly monitored, were estimated by SSA with accuracy, allowing the tracking of a suspect object.

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Cited By

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  • (2018)Comparative Study for the Effect of CPU Speed in Fog Networks2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT)10.1109/ISIICT.2018.8613284(1-5)Online publication date: Oct-2018
  • (2018)Data Missing Problem in Smart Surveillance Environment2018 International Conference on High Performance Computing & Simulation (HPCS)10.1109/HPCS.2018.00152(962-969)Online publication date: Jul-2018

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cover image ACM Other conferences
WebMedia '17: Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web
October 2017
522 pages
ISBN:9781450350969
DOI:10.1145/3126858
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • SBC: Brazilian Computer Society
  • CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
  • CGIBR: Comite Gestor da Internet no Brazil
  • CAPES: Brazilian Higher Education Funding Council

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2017

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Author Tags

  1. fog computing
  2. gap-filling
  3. machine-learning
  4. smart surveillance
  5. smart-city
  6. workload characterization

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  • Short-paper

Funding Sources

  • UFBA/CNPq

Conference

Webmedia '17
Sponsor:
  • SBC
  • CNPq
  • CGIBR
  • CAPES
Webmedia '17: Brazilian Symposium on Multimedia and the Web
October 17 - 20, 2017
RS, Gramado, Brazil

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WebMedia '17 Paper Acceptance Rate 38 of 138 submissions, 28%;
Overall Acceptance Rate 270 of 873 submissions, 31%

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Cited By

View all
  • (2018)Comparative Study for the Effect of CPU Speed in Fog Networks2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT)10.1109/ISIICT.2018.8613284(1-5)Online publication date: Oct-2018
  • (2018)Data Missing Problem in Smart Surveillance Environment2018 International Conference on High Performance Computing & Simulation (HPCS)10.1109/HPCS.2018.00152(962-969)Online publication date: Jul-2018

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