DocumentCode
948263
Title
Neural Networks for Improved Tracking
Author
Perlovsky, Leonid I. ; Deming, Ross W.
Author_Institution
Harvard Univ., Cambridge
Volume
18
Issue
6
fYear
2007
Firstpage
1854
Lastpage
1857
Abstract
In this letter, we have developed a neural network (NN) based upon modeling fields for improved object tracking. Models for ground moving target indicator (GMTI) tracks have been developed as well as neural architecture incorporating these models. The neural tracker overcomes combinatorial complexity of tracking in highly cluttered scenarios and results in about 20-dB (two orders of magnitude) improvement in signal-to-clutter ratio.
Keywords
computer vision; image motion analysis; neural nets; object detection; radar detection; radar tracking; target tracking; combinatorial complexity; ground moving target indicator; multitarget tracking; neural architecture; neural networks; object tracking; radar tracking; signal-to-clutter ratio; Combinatorial complexity; ground moving target indicator (GMTI) radar; multitarget tracking; neural networks (NNs);
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2007.903143
Filename
4359203
Link To Document