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Proceedings Paper

Efficient method for extracting object recognition metric from correlation filter output
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Paper Abstract

Correlation filters can be very effective for object recognition. However, these filters may become too computationally expensive when applied to large images, or large numbers of images, because they require Fourier transforms between the spatial and frequency domains. This paper makes the simplifying assumption of single object recognition and presents an algorithm designed to reduce complexity of computation and/or storage. The algorithm derives a frequency domain match metric as opposed to the standard approach of using the spatial correlation plane. The performance of the efficient algorithm is compared to that of the standard correlation filter algorithm, for both accuracy and computational requirements.

Paper Details

Date Published: 12 April 2004
PDF: 11 pages
Proc. SPIE 5437, Optical Pattern Recognition XV, (12 April 2004); doi: 10.1117/12.543538
Show Author Affiliations
Bhagavatula V. K. Vijaya Kumar, Carnegie Mellon Univ. (United States)
Jason Thornton, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 5437:
Optical Pattern Recognition XV
David P. Casasent; Tien-Hsin Chao, Editor(s)

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