1 March 1998 Feature space trajectory distorted object representation for classification and pose estimation
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Abstract
The feature space trajectory (FST) neural net is used for classification and pose estimation of the contents of regions of interest. The FST provides an attractive representation of distorted objects that overcomes problems present in other classifiers. We discuss its use in rejecting clutter inputs, selecting the number and identity of the aspect views most necessary to represent an object, and to distinguish between two objects, temporal image processing, automatic target recognition, and active vision.
David P. Casasent, David P. Casasent, Leonard Neiberg, Leonard Neiberg, Michael A. Sipe, Michael A. Sipe, } "Feature space trajectory distorted object representation for classification and pose estimation," Optical Engineering 37(3), (1 March 1998). https://doi.org/10.1117/1.602017 . Submission:
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