NDLI: Measuring Collectiveness via Refined Topological Similarity

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Issue 1s(Special Issue on Smartphone-Based Interactive Technologies, Systems, and Applications and Special Issue on Extended Best Papers from ACM Multimedia 2014), October 2015

Issue 1, August 2015

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 11

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 10

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 9

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) : Volume 8

Measuring Collectiveness via Refined Topological Similarity

Content Provider	ACM Digital Library
Author	Chen, Mulin Wang, Qi Li, Xuelong
Copyright Year	2016
Abstract	Crowd system has motivated a surge of interests in many areas of multimedia, as it contains plenty of information about crowd scenes. In crowd systems, individuals tend to exhibit collective behaviors, and the motion of all those individuals is called collective motion. As a comprehensive descriptor of collective motion, $\textit{collectiveness}$ has been proposed to reflect the degree of individuals moving as an entirety. Nevertheless, existing works mostly have limitations to correctly find the individuals of a crowd system and precisely capture the various relationships between individuals, both of which are essential to measure collectiveness. In this article, we propose a collectiveness-measuring method that is capable of quantifying collectiveness accurately. Our main contributions are threefold: (1) we compute relatively accurate collectiveness by making the tracked feature points represent the individuals more precisely with a point selection strategy; (2) we jointly investigate the spatial-temporal information of individuals and utilize it to characterize the topological relationship between individuals by manifold learning; (3) we propose a $\textit{stability}$ descriptor to deal with the irregular individuals, which influence the calculation of collectiveness. Intensive experiments on the simulated and real world datasets demonstrate that the proposed method is able to compute relatively accurate collectiveness and keep high consistency with human perception.
Starting Page	1
Ending Page	22
Page Count	22
File Format	PDF
ISSN	15516857
e-ISSN	15516865
DOI	10.1145/2854000
Volume Number	12
Issue Number	2
Journal	ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-03-03
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Multimedia Collectiveness Crowd analysis Feature extraction Manifold
Content Type	Text
Resource Type	Article
Subject	Hardware and Architecture Computer Networks and Communications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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