1 October 1997 Feature space trajectory for distorted-object classification and pose estimation in synthetic aperture radar
David P. Casasent, Rajesh Shenoy
Author Affiliations +
Classification and pose estimation of distorted input objects are considered. The feature space trajectory representation of distorted views of an object is used with a new eigenfeature space. For a distorted input object, the closest trajectory denotes the class of the input and the closest line segment on it denotes its pose. If an input point is too far from a trajectory, it is rejected as clutter. New methods for selecting Fukunaga-Koontz discriminant vectors, the number of dominant eigenvectors per class and for determining training, and test set compatibility are presented.
David P. Casasent and Rajesh Shenoy "Feature space trajectory for distorted-object classification and pose estimation in synthetic aperture radar," Optical Engineering 36(10), (1 October 1997). https://doi.org/10.1117/1.601520
Published: 1 October 1997
Lens.org Logo
CITATIONS
Cited by 24 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Databases

Synthetic aperture radar

Polarization

Signal to noise ratio

Data modeling

Optical engineering

Image segmentation

RELATED CONTENT


Back to Top