VCF: velocity correlation filter, towards space-borne satellite video tracking

Jia Shao, Bo Du*, Chen Wu, Jia Wu, Ruimin Hu, Xuelong Li

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

Tracking a moving target of interests from a space-borne satellite video is really a difficulty, since the target usually occupies only a few pixels in each frame of satellite video. Even it is a long train. Most state-of-the-art tracking algorithms mainly rely on luminance or color features, failing to handle this video tracking problem due to the extremely inadequate quality of targets features. To overcome this difficulty, we propose a velocity correlation filter (VCF), employing velocity feature and inertia mechanism to construct a kernel correlation filter for satellite video targets tracking. The velocity feature has a high discriminative ability to detect moving targets in satellite videos and the inertia mechanism can prevent model drift adaptively. Experimental results on three real satellite video datasets show our proposed approach outperforms state-of-the-art tracking methods with a more than 100 frames per second.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Multimedia and Expo, ICME 2018
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-6
Number of pages6
Volume2018-July
ISBN (Electronic)9781538617373
ISBN (Print)9781538617380
DOIs
Publication statusPublished - 8 Oct 2018
Event2018 IEEE International Conference on Multimedia and Expo, ICME 2018 - San Diego, United States
Duration: 23 Jul 201827 Jul 2018

Conference

Conference2018 IEEE International Conference on Multimedia and Expo, ICME 2018
CountryUnited States
CitySan Diego
Period23/07/1827/07/18

Keywords

  • Kernelized correlation filter
  • Model drift
  • Optical Flow
  • Satellite video tracking
  • Velocity feature

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