An online LC-KSVD based dictionary learning for multi-target tracking

Shuo Tang, Long Fei Zhang, Jia Li Yan, Xiang Wei Tan, Gang Yi Ding

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

5 Citations (Scopus)

Abstract

In this paper, we propose a novel framework for multi-objects tracking on solving two kind of challenges. One is how to discriminate different targets with similar appearance, the other is distinct the single target with serious variation over time. The proposed framework extracts discriminative appearance information of different objects from historical recordings of all tracked targets by a label consistent K-SVD (LC-KSVD) dictionary learning method. We validated our proposed framework on three publicly available video sequences with some state-of-the-art approaches. The experiment results showed that our proposed method achieves competitive results with 7.7% improvement in MOTP.

Original languageEnglish
Title of host publicationProceedings - 2016 International Conference on Information System and Artificial Intelligence, ISAI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages630-633
Number of pages4
ISBN (Electronic)9781509015856
DOIs
Publication statusPublished - 12 Jan 2017
Event2016 International Conference on Information System and Artificial Intelligence, ISAI 2016 - Hong Kong, China
Duration: 24 Jun 201626 Jun 2016

Publication series

NameProceedings - 2016 International Conference on Information System and Artificial Intelligence, ISAI 2016

Conference

Conference2016 International Conference on Information System and Artificial Intelligence, ISAI 2016
Country/TerritoryChina
CityHong Kong
Period24/06/1626/06/16

Keywords

  • Appearance model
  • Dictionary learning
  • Multi-objects tracking

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