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Marrying Tracking with ELM: A Metric Constraint Guided Multiple Feature Fusion Method
In this paper, we solve the problem from multi-view perspective by leveraging multi-view complementary and latent information, so as to be robust to the partial occlusion and background clutter especially when the objects are similar to the target, meanwhile addressing tracking drift.
Robust Tracking via Weighted Online Extreme Learning Machine
Therefore, our tracking method can fully learn both of the target object and background information to enhance the tracking performance, and it is evaluated in 20 challenge image sequences with different attributes including illumination, occlusion, deformation, etc., which achieves better performance than several state-of-the-art methods in terms of effectiveness and robustness.
A salt and pepper noise image denoising method based on the generative classification
In this paper, an image denoising algorithm is proposed for salt and pepper noise.
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