eprintid: 13256
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/32/56
datestamp: 2023-11-10 03:27:49
lastmod: 2023-11-10 03:27:49
status_changed: 2023-11-10 01:50:43
type: article
metadata_visibility: show
creators_name: Farooq, M.U.
creators_name: Saad, M.N.B.M.
creators_name: Malik, A.S.
creators_name: Salih Ali, Y.
creators_name: Khan, S.D.
title: Motion estimation of high density crowd using fluid dynamics
ispublished: pub
keywords: Anomaly detection; Behavioral research; Finite difference method; Fluid dynamics, Crowd analysis; Crowd behavior; Crowd behavior analysis; Crowd density; ME methods; Occlusion problems; On state, Motion estimation
note: cited By 7
abstract: Motion estimation (ME) being a fundamental process of crowd behavior analysis experienced real challenges at high densities due to visual ambiguities and occlusion problems etc. Various surveys reported in the past years summarize conventional ME methods for crowd behaviors at low/medium densities. In this paper, we focus on state-of-the-art fluid dynamics (FD) ME methods developed over the last one and the half-decade for high-density crowd analysis. A detailed discussion is provided on the development of FD ME methods explaining the strengths and weaknesses and viability of FD ME methods for anomaly detection at high crowd densities. Comprehensive experiments are performed comparing the performance of conventional and FD ME at varying crowd densities. Experimentation results show that conventional ME methods fail at high-density crowd whereas FD ME methods could estimate motion only at the global level. Still, research is required to meet the challenges of local ME at high crowd densities. © 2020, © 2020 The Royal Photographic Society.
date: 2020
publisher: Taylor and Francis Ltd.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086152756&doi=10.1080%2f13682199.2020.1767843&partnerID=40&md5=e42b0fbc623610ac7350b658925da2ca
id_number: 10.1080/13682199.2020.1767843
full_text_status: none
publication: Imaging Science Journal
volume: 68
number: 3
pagerange: 141-155
refereed: TRUE
issn: 13682199
citation:   Farooq, M.U. and Saad, M.N.B.M. and Malik, A.S. and Salih Ali, Y. and Khan, S.D.  (2020) Motion estimation of high density crowd using fluid dynamics.  Imaging Science Journal, 68 (3).  pp. 141-155.  ISSN 13682199