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Robust Object Tracking by Nonlinear Learning

Ma, Bo; Hu, Hongwei; Shen, Jianbing; Zhang, Yuping; Shao, Ling; Porikli, Fatih


We propose a method that obtains a discriminative visual dictionary and a nonlinear classifier for visual tracking tasks in a sparse coding manner based on the globally linear approximation for a nonlinear learning theory. Traditional discriminative tracking methods based on sparse representation learn a dictionary in an unsupervised way and then train a classifier, which may not generate both descriptive and discriminative models for targets by treating dictionary learning and classifier...[Show more]

CollectionsANU Research Publications
Date published: 2018-10
Type: Journal article
Source: IEEE Transactions on Neural Networks and Learning Systems
DOI: 10.1109/TNNLS.2017.2776124
Access Rights: Open Access


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