Location-specific transition distributions for tracking

Nathan Jacobs, Michael Dixon, Robert Pless

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations


Surveillance and tracking systems often observe the same scene over extended time periods. When object motion is constrained by the scene (for instance, cars on roads, or pedestrians on sidewalks), it is advantageous to characterize and use scene-specific and location-specific priors to aid the tracking algorithm. This paper develops and demonstrates a method for creating priors for tracking that are conditioned on the current location of the object in the scene. These priors can be naturally incorporated in a number of tracking algorithms to make tracking more efficient and more accurate. We present a novel method to sample from these priors and show performance improvements (in both efficiency and accuracy) for two different tracking algorithms in two different problem domains.

Original languageEnglish
Title of host publication2008 IEEE Workshop on Motion and Video Computing, WMVC
StatePublished - 2008
Event2008 IEEE Workshop on Motion and Video Computing, WMVC - Copper Mountain, CO, United States
Duration: Jan 8 2008Jan 9 2008

Publication series

Name2008 IEEE Workshop on Motion and Video Computing, WMVC


Conference2008 IEEE Workshop on Motion and Video Computing, WMVC
Country/TerritoryUnited States
CityCopper Mountain, CO

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software


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