A Collaborative Network of Correlation Filters for Object Recognition

Abhijit Mahalanobis; Alan J. Van Nevel

doi:10.1117/12.516097

A Collaborative Network of Correlation Filters for Object Recognition

Abhijit Mahalanobis
, Alan J. Van Nevel

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

In this paper, we introduce a novel method where several sensors and ATRs collaborate to recognize objects. Such an approach would be suitable for network centric application where the sensors and platforms can coordinate to optimize over all ATR performance. We use correlation pattern recognition techniques to facilitate the development of the concept, although other algorithms may be easily substituted. Essentially, a self-configuring network is proposed that positions the sensors optimally with respect to each other depending on the algorithm and the class of the object to be recognized. We show how such a network optimizes overall performance, and illustrate the scheme by means of examples.

Original language	English (US)
Pages (from-to)	219-226
Number of pages	8
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	5202
DOIs	https://doi.org/10.1117/12.516097
State	Published - 2003
Externally published	Yes
Event	Optical Information Systems - San Diego, CA, United States Duration: Aug 4 2003 → Aug 5 2003

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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10.1117/12.516097

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title = "A Collaborative Network of Correlation Filters for Object Recognition",

abstract = "In this paper, we introduce a novel method where several sensors and ATRs collaborate to recognize objects. Such an approach would be suitable for network centric application where the sensors and platforms can coordinate to optimize over all ATR performance. We use correlation pattern recognition techniques to facilitate the development of the concept, although other algorithms may be easily substituted. Essentially, a self-configuring network is proposed that positions the sensors optimally with respect to each other depending on the algorithm and the class of the object to be recognized. We show how such a network optimizes overall performance, and illustrate the scheme by means of examples.",

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year = "2003",

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pages = "219--226",

journal = "Proceedings of SPIE - The International Society for Optical Engineering",

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note = "Optical Information Systems ; Conference date: 04-08-2003 Through 05-08-2003",

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TY - JOUR

T1 - A Collaborative Network of Correlation Filters for Object Recognition

AU - Mahalanobis, Abhijit

AU - Van Nevel, Alan J.

PY - 2003

Y1 - 2003

N2 - In this paper, we introduce a novel method where several sensors and ATRs collaborate to recognize objects. Such an approach would be suitable for network centric application where the sensors and platforms can coordinate to optimize over all ATR performance. We use correlation pattern recognition techniques to facilitate the development of the concept, although other algorithms may be easily substituted. Essentially, a self-configuring network is proposed that positions the sensors optimally with respect to each other depending on the algorithm and the class of the object to be recognized. We show how such a network optimizes overall performance, and illustrate the scheme by means of examples.

AB - In this paper, we introduce a novel method where several sensors and ATRs collaborate to recognize objects. Such an approach would be suitable for network centric application where the sensors and platforms can coordinate to optimize over all ATR performance. We use correlation pattern recognition techniques to facilitate the development of the concept, although other algorithms may be easily substituted. Essentially, a self-configuring network is proposed that positions the sensors optimally with respect to each other depending on the algorithm and the class of the object to be recognized. We show how such a network optimizes overall performance, and illustrate the scheme by means of examples.

UR - https://www.scopus.com/pages/publications/1242263865

UR - https://www.scopus.com/pages/publications/1242263865#tab=citedBy

U2 - 10.1117/12.516097

DO - 10.1117/12.516097

M3 - Conference article

SN - 0277-786X

VL - 5202

SP - 219

EP - 226

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Optical Information Systems

Y2 - 4 August 2003 through 5 August 2003

ER -

A Collaborative Network of Correlation Filters for Object Recognition

Abstract

ASJC Scopus subject areas

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