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The problem considered is that of approximating an unknown system (plant) by learning the coeecients of a linear model from data collected on the plant performance , using the criterion of minimizing the sum of squared errors between predicted and actual performance. It is well known that the error surface is not unimodal, and that the estimated model may(More)
The sparse representation has been widely used in many areas including visual tracking. The part-based representation performs outstandingly by using non-holistic templates to against occlusion. This paper combined them and proposed a robust object tracking method using part-based sparsity model for tracking an object in a video sequence. In the proposed(More)
Online learned tracking is widely used to handle the appearance changes of object because of its adaptive ability. Learning to rank technique has attracted much attention recently in visual tracking. But the tracking method with online learning to rank suffers from the error accumulation problem during the self-training process. To solve this problem, we(More)
The bag-of-feature model has become a state-of-the-art method of visual classification. Visual codebooks can be used to capture image statistical information for object detection and classification, which is extracted from local image patches and based on the quantization of robust appearance descriptors. In this paper, more information of target objects(More)
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