Human motion tracking under indoor and outdoor surveillance system. (30th October 2020)

• Record Type: Journal Article
• Authors: Mrabti, Wafae; Tairi, Hamid; Morain-Nicolier, Frédéric; Bellach, Benaissa
• Is Part Of: International journal of innovative computing and applications. Volume 11:Number 4(2020)
• Page Start: 181
• Page End: 192
• Publication Date: 2020-10-30
• Subjects: features extraction -- motion model -- Kalman filter -- histogram of oriented gradient -- HOG -- support vector machines -- SVMs; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

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.