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Prediction-based Load Control and Balancing for Feature Extraction in Visual Sensor Networks
KTH, School of Electrical Engineering (EES), Communication Networks.ORCID iD: 0000-0001-8968-3976
KTH, School of Electrical Engineering (EES), Communication Networks.ORCID iD: 0000-0002-4876-0223
KTH, School of Electrical Engineering (EES), Communication Networks.ORCID iD: 0000-0002-2764-8099
2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We consider controlling and balancing the processing load in a visual sensor network (VSN) used for detecting local features, such as BRISK. We formulate a prediction problem with random missing data, and propose two regression-based algorithms for data reconstruction. Numerical results illustrate the performance of the proposed algorithms, and show that backward regression combined with the last value predictor can be used for controlling and balancing the processing load in VSNs with good performance.

Place, publisher, year, edition, pages
2014. 674-678 p.
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-156174DOI: 10.1109/ICASSP.2014.6853681ISI: 000343655300136Scopus ID: 2-s2.0-84905241294ISBN: 978-1-4799-2893-4 (print)ISBN: 978-147992892-7 OAI: oai:DiVA.org:kth-156174DiVA: diva2:765483
Conference
2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014; Florence; Italy; 4 May 2014 through 9 May 2014
Funder
EU, FP7, Seventh Framework Programme
Note

QC 20150123

Available from: 2014-11-24 Created: 2014-11-24 Last updated: 2015-01-23Bibliographically approved

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Eriksson, EmilDán, GyörgyFodor, Viktoria

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf