Title: Human motion tracking under indoor and outdoor surveillance system

Authors: Wafae Mrabti; Hamid Tairi; Frédéric Morain-Nicolier; Benaissa Bellach

Addresses: LIIAN, Department of Informatics, FSDM, Sidi Mohamed Ben Abdellah University, Fes, Morocco ' LIIAN, Department of Informatics, FSDM, Sidi Mohamed Ben Abdellah University, Fes, Morocco ' CReSTIC, URCA-IUT de Troyes, 9 Rue de Québec CS 90396, 10026 Troyes Cedex, France ' LSE2I Laboratory, National School of Applied Sciences, First Mohammed University, Oujda, Morocco

Abstract: This paper gives an overview of the various potential applications involved in human motion tracking. Also, a review of some relevant algorithms in this area are summarised based on three main components: the human target extraction, the features extraction, and the motion model. In addition, a proposed generative and discriminative human tracking method is presented. This proposed method is based on the hybridisation of Kalman filter (KF) and the support vector machines (SVMs). Numerous experiments illustrate the effectiveness of the proposed method against several state of the art trackers. These experiments are applied on several real world image sequences with various challenges that make the tracker vulnerable which are: partial and full occlusions, illumination changes, scale variation, out-of-plane, rotation, motion blur, low resolution, deformation, fast motion and background clutter.

Keywords: features extraction; motion model; Kalman filter; histogram of oriented gradient; HOG; support vector machines; SVMs.

DOI: 10.1504/IJICA.2020.111226

International Journal of Innovative Computing and Applications, 2020 Vol.11 No.4, pp.181 - 192

Received: 18 Jul 2019
Accepted: 26 Nov 2019
Published online: 16 Nov 2020 *

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