Object tracking based on kernel recursive least-squares with total error rate minimization

Se In Jang, Kangrok On, Andrew Beng Jin Teoh, Kar Ann Toh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an online tracking system which considers both target appearance and background changes simultaneously. Based on a kernel technique, a recursive formulation is proposed for total-error-rate (TER) minimization. Subsequently, the online solution is integrated into particle filtering to effectively distinguish the target object from the background. Our system is compared qualitatively and quantitatively with related existing methods on publicly available video sequences.

Original languageEnglish
Title of host publicationProceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013
Pages1415-1419
Number of pages5
DOIs
Publication statusPublished - 2013 Aug 19
Event2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013 - Melbourne, VIC, Australia
Duration: 2013 Jun 192013 Jun 21

Publication series

NameProceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013

Other

Other2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013
CountryAustralia
CityMelbourne, VIC
Period13/6/1913/6/21

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Jang, S. I., On, K., Beng Jin Teoh, A., & Toh, K. A. (2013). Object tracking based on kernel recursive least-squares with total error rate minimization. In Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013 (pp. 1415-1419). [6566588] (Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013). https://doi.org/10.1109/ICIEA.2013.6566588