Fast and Optimal Visual Tracking based on Spectral Method

Alexander A.S. Gunawan, Wisnu Jatmiko, Aniati Murni Arymurthy

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

1 Citation (Scopus)

Abstract

Visual object tracking is the process of continuously localizing visual object in a video sequence. We would like to investigate the problem of short-term model-free tracking which the main purpose is to track any object just based on an annotation box of object. Many factors affect the performance of the tracking algorithm. In the Visual Tracker Benchmark, there are eleven challenges in object tracking. There has not been a single tracker that successfully handles all of these scenarios. In addition, the tracker must be fast enough to be useful in real applications. We propose a new tracking algorithm within the Bayesian framework. The proposed algorithm is constructed by solving optimally particle filters (OPF) efficiently using spectral methods. Therefore, the constructed tracker is called as Spectral Tracker (ST). Although ST can efficiently compute object position, it cannot estimate the scale and rotation directly. To overcome this weakness, it is proposed to use multiple observation points simultaneously and to use information on the observation point movement to estimate scale and rotation. In the experiments, the performance of ST tracker was compared with 9 relevant trackers based on 100 data sets. The experimental results on on tracker performance show that increasing performance especially in tracker precision and success rate.

Original languageEnglish
Title of host publication2nd International Conference on Computer Science and Computational Intelligence, ICCSCI 2017
EditorsWdodo Budiharto, Dewi Suryani, Lili A. Wulandhari, Andry Chowanda, Alexander A.S. Gunawan, Novita Hanafiah, Hanry Ham, Meiliana
PublisherElsevier B.V.
Pages571-578
Number of pages8
ISBN (Print)9781510849914
DOIs
Publication statusPublished - 1 Jan 2017
Event2nd International Conference on Computer Science and Computational Intelligence, ICCSCI 2017 - Bali, Indonesia
Duration: 13 Oct 201714 Oct 2017

Publication series

NameProcedia Computer Science
Volume116
ISSN (Electronic)1877-0509

Conference

Conference2nd International Conference on Computer Science and Computational Intelligence, ICCSCI 2017
CountryIndonesia
CityBali
Period13/10/1714/10/17

Keywords

  • Bayesian framework
  • optimal particle filter
  • short-term model-free tracking
  • spectral method

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