Person and vehicle tracking in surveillance video

Andrew Miller, Arslan Basharat, Brandyn White, Jingen Liu, Mubarak Shah

Research output: Contribution to journalConference articlepeer-review


This evaluation for person and vehicle tracking in surveillance presented some new challenges. The dataset was large and very high-quality, but with difficult scene properties involving illumination changes, unusual lighting conditions, and complicated occlusion of objects. Since this is a well-researched scenario [1], our submission was based primarily on our existing projects for automated object detection and tracking in surveillance. We also added several new features that are practical improvements for handling the difficulties of this dataset.

Original languageEnglish (US)
Pages (from-to)174-178
Number of pages5
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4625 LNCS
StatePublished - Jul 28 2008
Externally publishedYes
Event2nd Annual Classifcation of Events Activities and Relationships, CLEAR 2007 and Rich Transcription, RT 2007 - Baltimore, MD, United States
Duration: May 8 2007May 11 2007

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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