Object Tracking With Joint Optimization of Representation and Classification

@article{Wang2015ObjectTW,
  title={Object Tracking With Joint Optimization of Representation and Classification},
  author={Qing Wang and Feng Chen and Wenli Xu and Ming-Hsuan Yang},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2015},
  volume={25},
  pages={638-650}
}
We present a novel algorithm that exploits joint optimization of representation and classification for robust tracking in which the goal is to minimize the least-squares reconstruction errors and discriminative penalties with regularized constraints. In this formulation, an object is represented by the sparse coefficients of local patches based on an overcomplete dictionary, and a classifier is learned to discriminate the target object from the background. To locate the target object in each… CONTINUE READING

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  • S. Baker, I. Matthews
  • Int. J. Comput. Vis., vol. 56, no. 3, pp. 221–255…
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