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Journal of Electronic Imaging • new

Enhanced compressed sensing for visual target tracking in wireless visual sensor networks
Author(s): Qiang Guo
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Paper Abstract

Moving object tracking in wireless sensor networks (WSNs) has been widely applied in various fields. Designing low-power WSNs for the limited resources of the sensor, such as energy limitation, energy restriction, and bandwidth constraints, is of high priority. However, most existing works focus on only single conflicting optimization criteria. An efficient compressive sensing technique based on a customized memory gradient pursuit algorithm with early termination in WSNs is presented, which strikes compelling trade-offs among energy dissipation for wireless transmission, certain types of bandwidth, and minimum storage. Then, the proposed approach adopts an unscented particle filter to predict the location of the target. The experimental results with a theoretical analysis demonstrate the substantially superior effectiveness of the proposed model and framework in regard to the energy and speed under the resource limitation of a visual sensor node.

Paper Details

Date Published: 19 December 2017
PDF: 6 pages
J. Electron. Imag. 26(6) 063028 doi: 10.1117/1.JEI.26.6.063028
Published in: Journal of Electronic Imaging Volume 26, Issue 6
Show Author Affiliations
Qiang Guo, China Criminal Police Univ. (China)

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