Object detection and tracking in real time videos

Christian R. Llano, Yuan Ren, Nazrul I Shaikh

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Object and human tracking in streaming videos are one of the most challenging problems in vision computing. In this article, we review some relevant machine learning algorithms and techniques for human identification and tracking in videos. We provide details on metrics and methods used in the computer vision literature for monitoring and propose a state-space representation of the object tracking problem. A proof of concept implementation of the state-space based object tracking using particle filters is presented as well. The proposed approach enables tracking objects/humans in a video, including foreground/background separation for object movement detection.

Original languageEnglish (US)
Pages (from-to)1-17
Number of pages17
JournalInternational Journal of Information Systems in the Service Sector
Issue number2
StatePublished - Apr 1 2019


  • Background Exclusion
  • OpenCV
  • Visual Object Tracking

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management


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