Context-based semantic labeling of Human-Vehicle Interactions in Persistent Surveillance Systems

Vinayak Elangovan, Amir Shirkhodaie

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

15 Scopus citations


The improved Situational awareness in Persistent Surveillance Systems (PSS) is an ongoing research effort of the Department of Defense. Most PSS generate huge volume of raw data and they heavily rely on human operators to interpret and inference data in order to detect potential threats. Many outdoor apprehensive activities involve vehicles as their primary source of transportation to and from the scene where a plot is executed. Vehicles are employed to bring in and take out ammunitions, supplies, and personnel. Vehicles are also used as a disguise, hide-out, a meeting place to execute threat plots. Analysis of the Human-Vehicle Interactions (HVI) helps us to identify cohesive patterns of activities representing potential threats. Identification of such patterns can significantly improve situational awareness in PSS. In our approach, image processing technique is used as the primary source of sensing modality. We use HVI taxonomy as a means for recognizing different types of HVI activities. HVI taxonomy may comprise multiple threads of ontological patterns. By spatiotemporal linking of ontological patterns, a HVI pattern is hypothesized to pursue a potential threat situation. The proposed technique generates semantic messages describing ontology of HVI. This paper also discusses a vehicle zoning technique for HVI semantic labeling and demonstrates efficiency and effectiveness of the proposed technique for identifying HVI.

Original languageEnglish (US)
Title of host publicationVisual Information Processing XX
StatePublished - 2011
EventVisual Information Processing XX - Orlando, FL, United States
Duration: Apr 26 2011Apr 27 2011

Publication series

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


OtherVisual Information Processing XX
Country/TerritoryUnited States
CityOrlando, FL

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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