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Proceedings Paper

Profiling sensor classification algorithm implementation on an embedded controller
Author(s): Robert K. Reynolds; David J. Russomanno; Srikant K. Chari; Carl E. Halford
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Paper Abstract

This paper provides a feasibility analysis and details of implementing a classification algorithm on an embedded controller for use with a profiling sensor. Such a profiling sensor has been shown to be a feasible approach to a low-cost persistent surveillance sensor for classifying moving objects such as humans, animals, or vehicles. The sensor produces data that can be used to generate object profiles as crude images or silhouettes, and/or the data can be subsequently automatically classified. This paper provides a feasibility analysis of a classification algorithm implemented on an embedded controller, which is packaged with a prototype version of a profiling sensor. Implementation of the embedded controller is a necessary extension of previous work for fielded profiling sensors and their appropriate applications. Field data is used to confirm accurate automated classification.

Paper Details

Date Published: 7 May 2010
PDF: 7 pages
Proc. SPIE 7694, Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR, 769413 (7 May 2010); doi: 10.1117/12.851900
Show Author Affiliations
Robert K. Reynolds, The Univ. of Memphis (United States)
David J. Russomanno, The Univ. of Memphis (United States)
Srikant K. Chari, The Univ. of Memphis (United States)
Carl E. Halford, The Univ. of Memphis (United States)


Published in SPIE Proceedings Vol. 7694:
Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR
Michael A. Kolodny, Editor(s)

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