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Neural network tracking and extension of positive tracking periodsFeature 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.
Document ID
20060043600
Acquisition Source
Jet Propulsion Laboratory
Document Type
Conference Paper
External Source(s)
Authors
Hanan, Jay C.
Chao, Tien-Hsin
Moreels, Pierre
Date Acquired
August 23, 2013
Publication Date
April 12, 2004
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Meeting Information
Meeting: International Society for Optical Engineering (SPIE) Defense and Security Symposium, Optical Pattern Recognition XV
Location: Orlando, FL
Country: United States
Start Date: April 12, 2004
End Date: April 16, 2004
Distribution Limits
Public
Copyright
Other
Keywords
feature extraction
autonomous tracking
neural network
data reduction
feature detector
target recognition

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