Se-In Jang

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This paper presents a visual object tracking system which is tolerant to external imaging factors such as illumination, scale, rotation, occlusion and background changes. Specifically, an integration of an online version of total-error-rate minimization based projection network with an observation model of particle filter is proposed to effectively(More)
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(More)
We treat tracking as a binary classification task in order to distinguish between an object to be tracked and the background. We propose to integrate an online learning based total-error-rate minimization method (OTER) with an observation model of particle filter for visual tracking. The particle filter is modeled using an affine dynamic model and an(More)
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