Hamd Ait Abdelali, Leila Essannouni, Fedwa Essannouni, Driss Aboutajdine, "A Novel Adaptive Object Tracking Method Based on Expected Likelihood Kernel," WSEAS Transactions on Signal Processing, vol. 11, pp. 45-51, 2015, DOI:
Hamd Ait Abdelali, Leila Essannouni, Fedwa Essannouni, Driss Aboutajdine. A Novel Adaptive Object Tracking Method Based on Expected Likelihood Kernel.
WSEAS Transactions on Signal Processing. 2015;11:45-51.
WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 11, 2015
A Novel Adaptive Object Tracking Method Based on Expected Likelihood Kernel
Authors: , , ,
Abstract: Visual tracking is a new line of broad research. It is required for advanced vision-based applications such as visual surveillance and vision-based human-robot interaction. In this paper, we propose a new method of object detection and tracking algorithm using Adaptive Expected Likelihood Kernel. In this algorithm we combine between the probability product kernels as a similarity measure, and the integral image to increase the speed of the algorithm.
Pages: 45-51 WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 11, 2015, Art. #6 DOI: *As the DOI is a unique identifier, it is already available in the pdf version.
**The DOI link will be activated in the first midst of January 2026.
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