TY - GEN
T1 - Object tracking based on kernel recursive least-squares with total error rate minimization
AU - Jang, Se In
AU - On, Kangrok
AU - Beng Jin Teoh, Andrew
AU - Toh, Kar Ann
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84881452057&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881452057&partnerID=8YFLogxK
U2 - 10.1109/ICIEA.2013.6566588
DO - 10.1109/ICIEA.2013.6566588
M3 - Conference contribution
AN - SCOPUS:84881452057
SN - 9781467363211
T3 - Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013
SP - 1415
EP - 1419
BT - Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013
T2 - 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013
Y2 - 19 June 2013 through 21 June 2013
ER -