TY  - JOUR
PB  - Taylor and Francis Ltd.
SN  - 13682199
EP  - 155
AV  - none
SP  - 141
TI  - Motion estimation of high density crowd using fluid dynamics
N1  - cited By 7
Y1  - 2020///
VL  - 68
JF  - Imaging Science Journal
A1  - Farooq, M.U.
A1  - Saad, M.N.B.M.
A1  - Malik, A.S.
A1  - Salih Ali, Y.
A1  - Khan, S.D.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086152756&doi=10.1080%2f13682199.2020.1767843&partnerID=40&md5=e42b0fbc623610ac7350b658925da2ca
ID  - scholars13256
KW  - Anomaly detection; Behavioral research; Finite difference method; Fluid dynamics
KW  -  Crowd analysis; Crowd behavior; Crowd behavior analysis; Crowd density; ME methods; Occlusion problems; On state
KW  -  Motion estimation
N2  - 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.
IS  - 3
ER  -