A multi-modality attributes representation scheme for Group Activity characterization and data fusion

Vinayak Elangovan, Amjad Alkilani, Amir Shirkhodaie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Proper characterization of human Group Activity (GA) interactions can help to detect and prevent certain pertinent threats efficiently. In this paper, we present a model-based scheme for robust group activity characterization. The proposed approach takes advantage of synergy of multi-sensors data to track and identify key individual and group activity events based on fusion of imagery and acoustic sensors data. Each activity event is attributed by a set of tagged features. By matching and correlating attributes of events, the model attempts to associate sensory observations to a priori known ontology. The proposed model benefits from a fusion process that achieves perceptual grouping of activities by spatiotemporal correlation and association of fragmented perceptions extracted from attributed events. In this paper, we present the results of our experimental work and demonstrate the effective and robustness of the decision fusion technique in terms of properly classifying group activities and generating semantic messages describing dynamics of human group activities that, in turn, improves situational awareness.

Original languageEnglish (US)
Title of host publicationIEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics
Subtitle of host publicationBig Data, Emergent Threats, and Decision-Making in Security Informatics
Pages85-90
Number of pages6
DOIs
StatePublished - Sep 9 2013
Event11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013 - Seattle, WA, United States
Duration: Jun 4 2013Jun 7 2013

Publication series

NameIEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics

Other

Other11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013
CountryUnited States
CitySeattle, WA
Period6/4/136/7/13

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems

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