Tracking motion-blurred targets in video

Shengyang Dai*, Ming Yang, Ying Wu, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Scopus citations


Many emerging applications require tracking targets in video. Most existing visual tracking methods do not work well when the target is motion-blurred (especially due to fast motion), because the imperfectness of the target's appearances invalidates the image matching model (or the measurement model) in tracking. This paper presents a novel method to track motion-blurred targets by taking advantage of the blurs without performing image restoration. Unlike the global blur induced by camera motion, this paper is concerned with the local blurs that are due to target's motion. This is a challenging task because the blurs need to be identified blindly. The proposed method addresses this difficulty by integrating signal processing and statistical learning techniques. The estimated blurs are used to reduce the search range by providing strong motion predictions and to localize the best match accurately by modifying the measurement models.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
Number of pages4
StatePublished - Dec 1 2006
Event2006 IEEE International Conference on Image Processing, ICIP 2006 - Atlanta, GA, United States
Duration: Oct 8 2006Oct 11 2006

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Other2006 IEEE International Conference on Image Processing, ICIP 2006
Country/TerritoryUnited States
CityAtlanta, GA


  • Frequency domain analysis
  • Image deblurring
  • Pattern recognition
  • Tracking

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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