Title: Object tracking in video via particle filter

Authors: Hamd Ait Abdelali; Fedwa Essannouni; Driss Aboutajdine

Addresses: LRIT, associated unit to CNRST (URAC 29), Faculty of Sciences, Mohammed V University in Rabat, Morocco ' LRIT, associated unit to CNRST (URAC 29), Faculty of Sciences, Mohammed V University in Rabat, Morocco ' LRIT, associated unit to CNRST (URAC 29), Faculty of Sciences, Mohammed V University in Rabat, Morocco

Abstract: In this paper, we present a new method for object tracking. We use an efficient local search scheme based on the probability product kernel using particle filter (PPKPF) to find the image region with a histogram most similar to the histogram of the tracked target. Experimental results verify the effectiveness of this proposed algorithm.

Keywords: computer vision; object tracking; particle filters; probability product kernels; histograms; integral images; local search.

DOI: 10.1504/IJIEI.2016.080514

International Journal of Intelligent Engineering Informatics, 2016 Vol.4 No.3/4, pp.340 - 353

Received: 08 Oct 2015
Accepted: 17 Feb 2016

Published online: 28 Nov 2016 *

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