GPU-enabled high performance feature modeling for ATR applications

Author

Dessauer, Michael P. ; Hitchens, Joshua ; Dua, Sumeet

Author_Institution

Dept. of Comput. Sci., Louisiana Tech Univ., Ruston, LA, USA

fYear

2010

fDate

14-16 July 2010

Firstpage

92

Lastpage

98

Abstract

Computational methods for automatic target recognition are constrained by the need to analyze increasingly high-dimensional sensor data in real time. Parallel processing has the potential to speed up computational bottlenecks in many automatic target recognition (ATR) methods. We will implement parallelized versions of target tracking methods and discuss gains in algorithm completion time.

Keywords

computer graphic equipment; coprocessors; image recognition; parallel processing; target tracking; GPU-enabled high performance feature modeling; algorithm completion time; automatic target recognition applications; computational bottlenecks; computational methods; graphical processing units; high-dimensional sensor data; parallel processing; target tracking methods; Computer vision; Feature extraction; Gabor filters; Graphics processing unit; Histograms; Optical filters; Target tracking; machine vision; object recognition; parallel processing; tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Aerospace and Electronics Conference (NAECON), Proceedings of the IEEE 2010 National

Conference_Location

Fairborn, OH

ISSN

0547-3578

Print_ISBN

978-1-4244-6576-7

Type

conf

DOI

10.1109/NAECON.2010.5712930

Filename

5712930