relation: https://khub.utp.edu.my/scholars/17417/
title: Anomaly Localization at High-Density Crowd Using Motion Shape Image (MSI)
creator: Farooq, M.U.
creator: Mohamad Saad, M.N.
creator: Daud Khan, S.
creator: Saleh, Y.
description: 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 �only� 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.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022
type: Article
type: PeerReviewed
identifier:   Farooq, M.U. and Mohamad Saad, M.N. and Daud Khan, S. and Saleh, Y.  (2022) Anomaly Localization at High-Density Crowd Using Motion Shape Image (MSI).  Lecture Notes in Electrical Engineering, 758.  pp. 889-906.  ISSN 18761100     
relation: 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
relation: 10.1007/978-981-16-2183-3₈₄
identifier: 10.1007/978-981-16-2183-3₈₄