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Demo : Enabling image analysis tasks in visual sensor networks

Baroffio, L. (author)
Canclini, A. (author)
Cesana, M. (author)
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Redondi, A. (author)
Tagliasacchi, M. (author)
Dán, György (author)
KTH,Kommunikationsnät
Eriksson, Emil (author)
KTH,Kommunikationsnät
Fodor, Viktoria (author)
KTH,Kommunikationsnät
Ascenso, J. (author)
Monteiro, P. (author)
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 (creator_code:org_t)
2014-11-04
2014
English.
In: Proceedings of the 8th ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2014. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450329255 ; , s. a46-
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • This demo showcases some of the results obtained by the GreenEyes project, whose main objective is to enable visual analysis on resource-constrained multimedia sensor networks. The demo features a multi-hop visual sensor network operated by BeagleBones Linux computers with IEEE 802.15.4 communication capabilities, and capable of recognizing and tracking objects according to two different visual paradigms. In the traditional compress-then-analyze (CTA) paradigm, JPEG compressed images are transmitted through the network from a camera node to a central controller, where the analysis takes place. In the alternative analyze-then-compress (ATC) paradigm, the camera node extracts and compresses local binary visual features from the acquired images (either locally or in a distributed fashion) and transmits them to the central controller, where they are used to perform object recognition/tracking. We show that, in a bandwidth constrained scenario, the latter paradigm allows to reach better results in terms of application frame rates, still ensuring excellent analysis performance.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)

Keyword

ARM
Binary local visual features
Object recognition
Object tracking
Visual sensor networks

Publication and Content Type

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kon (subject category)

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