Human activities monitoring at bus stops

G. Gasser, N. Bird, O. Masoud, Nikolaos P Papanikolopoulos

Research output: Contribution to journalConference articlepeer-review

16 Scopus citations


In this paper, we introduce a vision-based system to monitor for suspicious human activities at a bus stop. The system currently examines for drug dealing activity. To accomplish this goal, the system must measure how long individuals loiter around the bus stop. To facilitate this, the system must track individuals from the video feed, identify them, and keep a record of how long they spend at the bus stop. The system is broken into three distinct portions: background subtraction, object tracking, and human recognition. The background subtraction and object tracking modules use off-the-shelf algorithms and are shown to work well following people as they walk around a bus stop. The human recognition module segments the image of an individual into three portions corresponding to the head, torso, and legs. Using the median color of each of these regions, two people can be quickly compared to see if they are the same person.

Original languageEnglish (US)
Pages (from-to)90-95
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
Issue number1
StatePublished - 2004
EventProceedings- 2004 IEEE International Conference on Robotics and Automation - New Orleans, LA, United States
Duration: Apr 26 2004May 1 2004


  • Computer vision
  • Human activities recognition
  • Suspicious behavior monitoring
  • Visual recognition


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