Share Email Print

Optical Engineering • Open Access

Multispectral detection and tracking of multiple moving targets in cluttered urban environments
Author(s): Casey D. Demars; Michael C. Roggemann; Timothy C. Havens

Paper Abstract

This paper presents an algorithm for target detection and tracking by fusion of multispectral imagery. In all spectral bands, we build a background model of the pixel intensities using a Gaussian mixture model, and pixels not belonging to the model are classified as foreground pixels. Foreground pixels from the spectral bands are weighted and summed into a single foreground map and filtered to give the fused foreground map. Foreground pixels are grouped into target candidates and associated with targets from a tracking database by matching features from the scale-invariant feature transform. The performance of our algorithm was evaluated with a synthetically generated data set of visible, near-infrared, midwave infrared, and long-wave infrared video sequences. With a fused combination of the spectral bands, the proposed algorithm lowers the false alarm rate while maintaining high detection rates. All 12 vehicles were tracked throughout the sequence, with one instance of a lost track that was later recovered.

Paper Details

Date Published: 14 December 2015
PDF: 14 pages
Opt. Eng. 54(12) 123106 doi: 10.1117/1.OE.54.12.123106
Published in: Optical Engineering Volume 54, Issue 12
Show Author Affiliations
Casey D. Demars, Michigan Technological Univ. (United States)
Michael C. Roggemann, Michigan Technological Univ. (United States)
Timothy C. Havens, Michigan Technological Univ. (United States)

© SPIE. Terms of Use
Back to Top