@inproceedings{3dc8c470f21845708d291fdd3d3444dd,
title = "Visual moving object tracking via sparse representation based trackers: A comparative study",
abstract = "Motion tracking is one of the richest research fields in computer vision. Indeed, numerous algorithms have been implemented for object tracking. In this paper we briefly present the principles of three recent methods treating the motion tracking: The discriminative sparse similarity map (DSS map), the probability continuous outlier model (PCOM) and the L2 regularized least square (L2-RLS). And then we evaluate them quantitatively and qualitatively by testing them on nine image sequences which including various challenging factors. In order to achieve that, two most popular criterions: The center location error and the overlap rate are computed for each method. The most effective tracker is the one that has the greatest overlap rate and the smallest center error.",
keywords = "appearance model, motion model, object tracking, occlusion handling, sparse representation",
author = "Driss Moujahid and Omar Elharrouss and Hamid Tairi",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 3rd IEEE World Conference on Complex Systems, WCCS 2015 ; Conference date: 23-11-2015 Through 25-11-2015",
year = "2016",
month = jun,
day = "1",
doi = "10.1109/ICoCS.2015.7483285",
language = "English",
series = "Proceedings of 2015 IEEE World Conference on Complex Systems, WCCS 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Mohamed Nemiche and Mohamed Essaaidi",
booktitle = "Proceedings of 2015 IEEE World Conference on Complex Systems, WCCS 2015",
}