Tracking multiple objects in urban traffic environments using dense stereo and optical flow

Stereo vision based sensors provide large amounts of data, a fact which is advantageous when trying to extract semantic information about the imaged scene. However, these data are corrupted by errors, caused especially by the uncertainties in the stereo reconstruction process. Temporal information can be used in order to minimize these errors. This paper presents an advanced object model, a novel association mechanism and the design of a Kalman filter based tracking algorithm, for tracking multiple objects, in complex, urban traffic scenarios.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 791-796
  • Monograph Title: 14th International IEEE Conference on Intelligent Transportation Systems (ITSC 2011)

Subject/Index Terms

Filing Info

  • Accession Number: 01565405
  • Record Type: Publication
  • ISBN: 9781457721984
  • Files: TRIS
  • Created Date: May 20 2015 2:32PM