Multi-camera human activity monitoring

Loren Fiore, Duc Fehr, Robot Bodor, Andrew Drenner, Guruprasad Somasundaram, Nikolaos Papanikolopoulos

Research output: Contribution to journalArticlepeer-review

77 Scopus citations


With the proliferation of security cameras, the approach taken to monitoring and placement of these cameras is critical. This paper presents original work in the area of multiple camera human activity monitoring. First, a system is presented that tracks pedestrians across a scene of interest and recognizes a set of human activities. Next, a framework is developed for the placement of multiple cameras to observe a scene. This framework was originally used in a limited X, Y, pan formulation but is extended to include height (Z) and tilt. Finally, an active dual-camera system for task recognition at multiple resolutions is developed and tested. All of these systems are tested under real-world conditions, and are shown to produce usable results.

Original languageEnglish (US)
Pages (from-to)5-43
Number of pages39
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Issue number1
StatePublished - May 2008

Bibliographical note

Funding Information:
This work has been supported by the NSF through grants #IIS-0219863, #CNS-0224363, #CNS-0324864, #IIP-0443945, #CNS-0420836, #IIP-0726109, and #CNS-0708344.


  • Camera placement
  • Human activity recognition
  • Pedestrian tracking
  • Surveillance


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