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Proceedings Paper

Neural network tracking and extension of positive tracking periods
Author(s): Jay C. Hanan; Tien-Hsin Chao; Pierre Moreels
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Paper Abstract

Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.

Paper Details

Date Published: 12 April 2004
PDF: 5 pages
Proc. SPIE 5437, Optical Pattern Recognition XV, (12 April 2004); doi: 10.1117/12.548081
Show Author Affiliations
Jay C. Hanan, Jet Propulsion Lab. (United States)
Tien-Hsin Chao, Jet Propulsion Lab. (United States)
Pierre Moreels, California Institute of Technology (United States)

Published in SPIE Proceedings Vol. 5437:
Optical Pattern Recognition XV
David P. Casasent; Tien-Hsin Chao, Editor(s)

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