Automated Real-Time Detection of Potentially Suspicious Behavior in Public Transport Areas

Detection of suspicious activities in public transport areas using video surveillance has attracted an increasing level of attention. In general, automated offline video processing systems have been used for post-event analysis, such as forensics and riot investigations. However, very little has been achieved regarding real-time event recognition. In this paper, the authors introduce a framework that processes raw video data received from a fixed color camera installed at a particular location, which makes real-time inferences about the observed activities. First, the proposed framework obtains 3-D object-level information by detecting and tracking people and luggage in the scene using a real-time blob matching technique. Based on the temporal properties of these blobs, behaviors and events are semantically recognized by employing object and interobject motion features. A number of types of behavior that are relevant to security in public transport areas have been selected to demonstrate the capabilities of this approach. Examples of these are abandoned and stolen objects, fighting, fainting, and loitering. Using standard public data sets, the experimental results presented here demonstrate the outstanding performance and low computational complexity of this approach. The advantages over other approaches in the literature also are discussed.

• Record URL:
  • https://doi.org/10.1109/TITS.2012.2228640
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Authors:
  • Elhamod, Mohannad
  • Levine, Martin D
• Publication Date: 2013-6

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 688-699
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 14
  • Issue Number: 2
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Behavior; Detection and identification systems; Motion; Real time information; Security; Surveillance; Video
• Subject Areas: Data and Information Technology; Public Transportation; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01524679
• Record Type: Publication
• Files: TLIB, TRIS
• Created Date: May 1 2014 4:36PM