Visual Vehicle Tracking via Deep Learning and Particle Filter

TitreVisual Vehicle Tracking via Deep Learning and Particle Filter
Publication TypeJournal Article
Year of Publication2021
AuthorsH. Abdelali, A, Bourja, O, Haouari, R, Derrouz, H, Zennayi, Y, Bourzex, F, R. Thami, OHaj
JournalAdvances in Intelligent Systems and Computing
Volume1188
Pagination517-526
Mots-clésDeep learning, Monte Carlo methods, Particle filter, Real-time application, Research topics, Soft computing, Vehicles
Abstract

Visual vehicle tracking is one of the most challenging research topics in computer vision. In this paper, we propose a novel and efficient approach based on the particle filter technique and deep learning for multiple vehicle tracking, where the main focus is to associate vehicles efficiently for online and real-time applications. Experimental results illustrate the effectiveness of the system we are proposing. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85096559933&doi=10.1007%2f978-981-15-6048-4_45&partnerID=40&md5=51a9b5456004a8cdb4bc0a5256e17dc9
DOI10.1007/978-981-15-6048-4_45
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