TY  - JOUR
N1  - cited By 0; Conference of 1st International Conference on Artificial Intelligence for Smart Community, AISC 2020 ; Conference Date: 17 December 2020 Through 18 December 2020; Conference Code:286319
TI  - Anomaly Localization at High-Density Crowd Using Motion Shape Image (MSI)
SP  - 889
AV  - none
EP  - 906
PB  - Springer Science and Business Media Deutschland GmbH
SN  - 18761100
N2  - Anomaly localization plays a critical role if a disaster occurs in a high-density crowd to efficiently rescue the crowd from the right location. This paper enriches anomaly localization by introducing new localization features, in addition to the â??onlyâ?? localization feature of source/start point detection existing literature offers. New features introduced include crowd density estimation in localized regions and direction/angle of a localized region. A motion shape image (MSI) based approach is introduced for localization and features detection and experimentation is performed on benchmark and our proposed high-density crowd datasets. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ID  - scholars17417
KW  - Anomaly; Anomaly localizations; Divergence; FTLE; LCS; Localisation; Localised; Motion shape image; Point detection; Start point
KW  -  Feature extraction
A1  - Farooq, M.U.
A1  - Mohamad Saad, M.N.
A1  - Daud Khan, S.
A1  - Saleh, Y.
JF  - Lecture Notes in Electrical Engineering
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142684569&doi=10.1007%2f978-981-16-2183-3_84&partnerID=40&md5=d3ada1a94ec67eec21d02a8ffe24264d
VL  - 758
Y1  - 2022///
ER  -