Open AccessIntegrating Local Binary Patterns into Normalized Moment of Inertia for Updating Tracking Templates
Author(s) -
Song Huajun,
Xiao Botao,
Hu Qinzhen,
Ren Peng
Publication year - 2016
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2016.07.016
Subject(s) - moment of inertia , binary number , template , local binary patterns , moment (physics) , tracking (education) , inertia , computer science , artificial intelligence , mathematics , physics , histogram , arithmetic , classical mechanics , psychology , pedagogy , image (mathematics) , programming language
This paper presents an efficient visual tracking framework which is robust to rotation, scale variation and occlusion. The target template is characterized by Local binary patterns (LBP), which exhibit invariance to rotation. The LBP features are then integrated into the Normalized moment of inertia (NMI) to decide whether the template requires update. This procedure enables an adaptive template matching strategy which addresses the tracking failures arising from scale variations. Kalman filtering is exploited for predicting the trajectory of the target when it is occluded. The matching efficiency is achieved by applying a locally pyramid searching scheme. Experimental results validate the efficiency and effectiveness of our tracking framework.