Robust Visual Tracking Based on Incremental Tensor Subspace Learning

@article{Li2007RobustVT,
  title={Robust Visual Tracking Based on Incremental Tensor Subspace Learning},
  author={Xi Li and Weiming Hu and Zhongfei Zhang and Xiaoqin Zhang and Guan Luo},
  journal={2007 IEEE 11th International Conference on Computer Vision},
  year={2007},
  pages={1-8}
}
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspace analysis is incorporated into the multilinear framework which offline constructs a representation of image ensembles using high-order tensors. This reduces spatio-temporal redundancies substantially, whereas the computational and memory cost is high. In this paper, we present an effective online tensor subspace… CONTINUE READING
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