Adaptive Fuzzy Weighted Template Matching Using Invariant Features for a Tracking Application
Adaptive Fuzzy Weighted Template Matching Using Invariant Features for a Tracking Application
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Abstract
One of the common research topics for surveillance systems is tracking of a target object. Motions of both observer and target make the problem difficult to handle. In this paper, proposed algorithm tracks a target object on consecutive frames taken from a camera embedded on an unmanned aerial vehicle. Adaptive-fuzzy weighted sum of square distances (SSDs) are utilized for template matching process. SSD is computed by the pseudo-Zernike moments of the reference template and possible matching template around the search point. Fuzzy weights are obtained by taking the advantage of circular projection features. An adaptive fuzzy system is realized by updating the weights of the defuzzifier. Proposed method provides center point of the best matching template which represents the target object to be tracked. Tracking is accomplished under the presence of illumination changes and parallax, and it is seen that the proposed algorithm yields satisfactorily small errors. © 2010 IFAC.
Description
Keywords
Adaptive fuzzy, Circular projections, Pseudo-Zernike moments, Template matching, Tracking
Fields of Science
Citation
10th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, ALCOSP 2010, 26 August 2010 through 28 August 2010, Antalya, 105476
WoS Q
Scopus Q
Volume
1
Issue
PART 1
Start Page
259
End Page
264
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