Robust infrared vehicle tracking across target pose change using L1 regularization

@article{Ling2010RobustIV,
  title={Robust infrared vehicle tracking across target pose change using L1 regularization},
  author={Haibin Ling and Li Bai and Erik Blasch and Xue Mei},
  journal={2010 13th International Conference on Information Fusion},
  year={2010},
  pages={1-8}
}
In this paper, we propose a robust vehicle tracker for Infrared (IR) videos motivated by the recent advance in compressive sensing (CS). The new eL1-PF tracker solves a sparse model representation of moving targets via L1 regularized least squares. The sparse-model solution addresses real-world environmental challenges such as image noises and partial occlusions. To further improve tracking performance for frame-to-frame sequences involving large target pose changes, two extensions to the… CONTINUE READING
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