Recognition of human-vehicle interactions in group activities via multi-attributed semantic message generation

Vinayak Elangovan, Amir Shirkhodaie

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

1 Scopus citations


Improved Situational awareness is a vital ongoing research effort for the U.S. Homeland Security for the past recent years. Many outdoor anomalous activities involve vehicles as their primary source of transportation to and from the scene where a plot is executed. Analysis of dynamics of Human-Vehicle Interaction (HVI) helps to identify correlated patterns of activities representing potential threats. The objective of this paper is bi-folded. Primarily, we discuss a method for temporal HVI events detection and verification for generation of HVI hypotheses. To effectively recognize HVI events, a Multi-attribute Vehicle Detection and Identification technique (MVDI) for detection and classification of stationary vehicles is presented. Secondly, we describe a method for identification of pertinent anomalous behaviors through analysis of state transitions between two successively detected events. Finally, we present a technique for generation of HVI semantic messages and present our experimental results to demonstrate the effectiveness of semantic messages for discovery of HVI in group activities.

Original languageEnglish (US)
Title of host publicationNext-Generation Analyst III
EditorsTimothy P. Hanratty, James Llinas, Barbara D. Broome, David L. Hall
ISBN (Electronic)9781628416152
StatePublished - Jan 1 2015
EventNext-Generation Analyst III - Baltimore, United States
Duration: Apr 20 2015Apr 21 2015

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherNext-Generation Analyst III
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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