Feature space trajectory for distorted-object classification and pose estimation in synthetic aperture radar

David P. Casasent; Rajesh Shenoy

doi:10.1117/1.601520

1 October 1997 Feature space trajectory for distorted-object classification and pose estimation in synthetic aperture radar

David P. Casasent, Rajesh Shenoy

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Optical Engineering, Vol. 36, Issue 10, (October 1997). https://doi.org/10.1117/1.601520

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.

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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

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