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Correlation filter-based tracking methods have been intensively investigated for their high efficiency and robustness. However, a single feature-based tracker cannot adapt to challenging situations, such as severe deformation, rotation, and illumination variations. Besides, a simple linear interpolation-based model updating mechanism is prone to model degradation, and consequently tracker drifting...
We propose a novel superpixel extraction method named USEQ to generate regular and compact superpixels. To reduce the computational burden of iterative optimization procedures used in most recent approaches, the spatial and color quantizations are performed in advance to represent pixels and superpixels. Maximum a posteriori estimation in both pixel and region levels is then adopted to aggregate pixels...
Correlation filter based tracking method has been widely used for its high efficiency and robustness. However, reducing model drifting while achieving both high robustness and fast scale estimation is still an open problem. In this paper, we represent the target in kernel feature space and train a classifier on a scale pyramid to achieve adaptive scale estimation. We then integrate three complementary...
Bayesian estimation for parameters and the reliability of products for which the performance degradation process modeled by wiener process is obtained based on linex loss function. Using both non-informative and conjugate prior distribution, several Bayesian estimates under squared error and linex loss functions are computed. Finally, these Bayesian estimates are compared through the mean squared...
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