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This paper considers the task of closed curve filtering for visual tracking. Segmentation-based visual tracking strategies provide the closed curve measurements to filter. This paper discusses the derivation of a local, linear description for planar curve variation and curve uncertainty. It consists of a family of non-intersecting trajectories transverse to a given curve. Along one of the single-dimensional...
Robust visual tracking has become an important topic of research in computer vision. A novel method for robust object tracking, GATE [11], improves object tracking in complex environments using the particle filtering and the level set-based active contour method. GATE creates a spatial prior in the state space using shape information of the tracked object to filter particles in the state space in...
Accurate visual object tracking through long sequences is a challenging task since object's appearance changes and complex motion happens. We present mixture motion model and incorporate observation model within the Monte Carlo framework to achieve robust visual tracking. The mixture motion model which employs important history motion information of the target is built according to a motion measurement...
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