Who Knows Who - Inverting the Social Force Model for Finding Groups
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00187147" target="_blank" >RIV/68407700:21230/11:00187147 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Who Knows Who - Inverting the Social Force Model for Finding Groups
Original language description
Social groups based on friendship or family relations are very common phenomena in human crowds and a valuable cue for a crowd activity recognition system. In this paper we present an algorithm for automatic on-line inference of social groups from observed trajectories of individual people. The method is based on the Social Force Model (SFM) - widely used in crowd simulation applications -- which specifies several attractive and repulsive forces influencing each individual relative to the other pedestrians and their environment. The main contribution of the paper is an algorithm for inference of the social groups (parameters of the SFM) based on analysis of the observed trajectories through attractive or repulsive forces which could lead to such behaviour. The proposed SFM-based method shows its clear advantage especially in more crowded scenarios where other state-of-the-art methods fail. The applicability of the algorithm is illustrated on an abandoned bag scenario.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/7E10045" target="_blank" >7E10045: Massive Sets of Heuristics for Machine Learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)
ISBN
978-1-4673-0063-6
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
830-837
Publisher name
IEEE Computer Society Press
Place of publication
Los Alamitos
Event location
Barcelona
Event date
Nov 6, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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