Neural network tracking and extension of positive tracking periods
- Creators
- Hanan, Jay C.
- Chao, Tien-Hsin
- Moreels, Pierre
- Others:
- Casasent, David P.
- Chao, Tien-Hsin
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.
Additional Information
© 2004 Society of Photo-optical Instrumentation Engineers (SPIE). The research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.Attached Files
Published - 233.pdf
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Additional details
- Eprint ID
- 92290
- Resolver ID
- CaltechAUTHORS:20190115-140213505
- NASA/JPL/Caltech
- Created
-
2019-01-15Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field
- Series Name
- Proceedings of SPIE
- Series Volume or Issue Number
- 5437