Improved training for target detection using Fukunaga-Koontz transform and distance classifier correlation filter

M. I. Elbakary; M. S. Alam; M. S. Aslan

doi:10.1117/12.778370

17 March 2008 Improved training for target detection using Fukunaga-Koontz transform and distance classifier correlation filter

M. I. Elbakary, M. S. Alam, M. S. Aslan

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Proceedings Volume 6977, Optical Pattern Recognition XIX; 69770F (2008) https://doi.org/10.1117/12.778370
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

In a FLIR image sequence, a target may disappear permanently or may reappear after some frames and crucial information such as direction, position and size related to the target are lost. If the target reappears at a later frame, it may not be tracked again because the 3D orientation, size and location of the target might be changed. To obtain information about the target before disappearing and to detect the target after reappearing, distance classifier correlation filter (DCCF) is trained manualy by selecting a number of chips randomly. This paper introduces a novel idea to eliminates the manual intervention in training phase of DCCF. Instead of selecting the training chips manually and selecting the number of the training chips randomly, we adopted the K-means algorithm to cluster the training frames and based on the number of clusters we select the training chips such that a training chip for each cluster. To detect and track the target after reappearing in the field-ofview ,TBF and DCCF are employed. The contduced experiemnts using real FLIR sequences show results similar to the traditional agorithm but eleminating the manual intervention is the advantage of the proposed algorithm.

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M. I. Elbakary, M. S. Alam, and M. S. Aslan "Improved training for target detection using Fukunaga-Koontz transform and distance classifier correlation filter", Proc. SPIE 6977, Optical Pattern Recognition XIX, 69770F (17 March 2008); https://doi.org/10.1117/12.778370

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KEYWORDS

Target detection

Detection and tracking algorithms

Image filtering

Forward looking infrared

Matrices

3D acquisition

Algorithm development

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