Multi-Modal Sparse Tracking by Jointing Timing and Modal Consistency

Jiajun LI, Bin FANG*, Mingliang ZHOU

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

In this paper, we propose a multi-modal sparse tracking by jointing timing and modal consistency to locate the target location with the similarity of multiple local appearances. First, we propose an alignable patching strategy for red-green-blue (RGB) color mode and thermal infrared mode to adapt to the local changes of the target. Second, we propose a consistency expression of the corresponding aligned patches between the modes and the correlation of the gaussian mapping within mode to reconstruct the target judgment likelihood function. Finally, we propose an updating scenario based on timing correlation and mode sparsity to fit with the target changes. According to the experimental results, significant improvement in terms of tracking accuracy can be achieved on average compared with the state-of-the-art algorithms. The source code of our algorithm is available on https://github.com/Liincq/tracker.

Original languageEnglish
Article number2251008
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume36
Issue number6
Early online date20 Apr 2022
DOIs
Publication statusPublished - May 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 World Scientific Publishing Company.

Keywords

  • Modal consistency
  • Object tracking
  • Sparse representation

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