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Proceedings Paper

KL Techniques For Optimal Processing Of Time Sequential Imagery
Author(s): Pieter Vermeulen; David Casasent
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Paper Abstract

Time sequential imagery is difficult to analyze, because of its high dimesionality. This paper advances a new algorithm that screens input data in an intelligent way, discards data with negligible information and uses the remaining images to represent the sequence in an optimal compact form. We present data to illustrate how this algorithm can be used to do novelty filtering, novelty detection, segmentation, background independent modelling and classification.

Paper Details

Date Published: 10 March 1989
PDF: 14 pages
Proc. SPIE 1007, Mobile Robots III, (10 March 1989); doi: 10.1117/12.949094
Show Author Affiliations
Pieter Vermeulen, Carnegie Mellon University (United States)
David Casasent, Carnegie Mellon University (United States)


Published in SPIE Proceedings Vol. 1007:
Mobile Robots III
William J. Wolfe, Editor(s)

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