Learning Collaborative Sparse Representation for Grayscale-Thermal Tracking

@article{Li2016LearningCS,
  title={Learning Collaborative Sparse Representation for Grayscale-Thermal Tracking},
  author={Chenglong Li and Hui Cheng and Shiyi Hu and Xiaobai Liu and Jin Tang and Liang Lin},
  journal={IEEE Transactions on Image Processing},
  year={2016},
  volume={25},
  pages={5743-5756}
}
Integrating multiple different yet complementary feature representations has been proved to be an effective way for boosting tracking performance. This paper investigates how to perform robust object tracking in challenging scenarios by adaptively incorporating information from grayscale and thermal videos, and proposes a novel collaborative algorithm for online tracking. In particular, an adaptive fusion scheme is proposed based on collaborative sparse representation in Bayesian filtering… CONTINUE READING

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