Combining evidence for social situation detection

Georg Groh, Christoph Fuchs, Alexander Lehmann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Social Situations (SSs) are social context models indicating n-ary social interaction on small spatio-temporal scales detected by means of Social Signal Processing (SSP). We discuss the problem of how to combine evidence from several sensorsources for the benefit of algorithmic assessment of SS in a distributed agent-based Social Networking scenario. We propose a solution based on Subjective Logic (SL) that mediates between exchanging & processing of (a) raw low level sensor data, of (b) intermediate results of'sub- symbolic'probabilistic models typically used for SSP, and of (c) the final'symbolic'SS models. We evaluate key aspects of the approach on the basis of a social experiment, combining audio-based and geometry-of-interactionbased methods for SS detection.

Original languageEnglish
Title of host publicationProceedings - 2011 IEEE International Conference on Privacy, Security, Risk and Trust and IEEE International Conference on Social Computing, PASSAT/SocialCom 2011
Pages742-747
Number of pages6
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2011 and 2011 IEEE International Conference on Social Computing, SocialCom 2011 - Boston, MA, United States
Duration: 9 Oct 201111 Oct 2011

Publication series

NameProceedings - 2011 IEEE International Conference on Privacy, Security, Risk and Trust and IEEE International Conference on Social Computing, PASSAT/SocialCom 2011

Conference

Conference2011 IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2011 and 2011 IEEE International Conference on Social Computing, SocialCom 2011
Country/TerritoryUnited States
CityBoston, MA
Period9/10/1111/10/11

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