21 July 2016 Automatic target tracking in forward-looking infrared video sequences using tuned basis functions
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Abstract
Tuned basis function (TBF) is a powerful technique for classification of two classes by transforming them into a new space, where both classes will have complementary eigenvectors. A target discrimination technique can be described based on these complementary eigenvector analyses under two classes: (1) target and (2) background clutter, where basis functions that best represent the desired targets form one class while the complementary basis functions form the second class. Since the TBF does not require pixel-based preprocessing, it provides significant advantages for target tracking applications. Furthermore, efficient eigenvector selection and subframe segmentation significantly reduce the computation burden of the target tracking algorithm. The performance of the proposed TBF-based target tracking algorithm has been tested using real-world forward looking infrared video sequences.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2016/$25.00 © 2016 SPIE
Abdullah Bal and Mohammad S. Alam "Automatic target tracking in forward-looking infrared video sequences using tuned basis functions," Optical Engineering 55(7), 073102 (21 July 2016). https://doi.org/10.1117/1.OE.55.7.073102
Published: 21 July 2016
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Cited by 1 scholarly publication.
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KEYWORDS
Forward looking infrared

Target detection

Detection and tracking algorithms

Video

Automatic tracking

Optical tracking

Cameras

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