Orderless and blurred visual tracking via spatio-temporal context

Manna Dai, Peijie Lin, Lijun Wu, Zhicong Chen, Songlin Lai, Jie Zhang, Shuying Cheng, Xiangjian He

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

3 Citations (Scopus)


In this paper, a novel and robust method which exploits the spatiotemporal context for orderless and blurred visual tracking is presented. This lets the tracker adapt to both rigid and deformable objects on-line even if the image is blurred. We observe that a RGB vector of an image which is resized into a small fixed size can keep enough useful information. Based on this observation and computational reasons, we propose to resize the windows of both template and candidate target images into 2×2 and use Euclidean Distance to compute the similarity between these two RGB image vectors for the preliminary screening. We then apply spatio-temporal context based on Bayesian framework to further compute a confidence map for obtaining the best target location. Experimental results on challenging video sequences in MATLAB without code optimization show the proposed tracking method outperforms eight state-of-the-art methods.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 21st International Conference, MMM 2015, Proceedings
EditorsXiangjian He, Dacheng Tao, Muhammad Abul Hasan, Suhuai Luo, Changsheng Xu, Jie Yang
PublisherSpringer Verlag
Number of pages12
ISBN (Electronic)9783319144443
Publication statusPublished - 2015
Externally publishedYes
Event21st International Conference on MultiMedia Modeling, MMM 2015 - Sydney, Australia
Duration: 5 Jan 20157 Jan 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st International Conference on MultiMedia Modeling, MMM 2015


  • Bayesian framework
  • Euclidean Distance
  • Resize
  • Spatio-temporal-context

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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