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To reduce the computation and to improve the performance of object detection and tracking algorithm with object appearance variation, a tracker based on sparse eigenbasis is proposed. According to the compressive sensing theory, the objects are described in a low-dimensional sub-space representation based on Karhunen–Loeve transform learned online. Meanwhile, combining the Bayesian inference, an adaptive...
This paper proposes a new unsupervised image segmentation method by using Bhattacharyya distance-based irregular pyramid, termed as ‘BDIP’ algorithm. The proposed BDIP algorithm obtains a suboptimal labelling solution under the condition that the number of segments is not manually given. It hierarchically builds each level of the irregular pyramid, with the result that the final segments emerge as...
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