Tracking Social Groups Within and Across Cameras

@article{Solera2017TrackingSG,
  title={Tracking Social Groups Within and Across Cameras},
  author={Francesco Solera and Simone Calderara and Ergys Ristani and Carlo Tomasi and Rita Cucchiara},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2017},
  volume={27},
  pages={441-453}
}
We propose a method for tracking groups from single and multiple cameras with disjointed fields of view. Our formulation follows the tracking-by-detection paradigm in which groups are the atomic entities and are linked over time to form long and consistent trajectories. To this end, we formulate the problem as a supervised clustering problem in which a structural SVM classifier learns a similarity measure appropriate for group entities. Multicamera group tracking is handled inside the framework… CONTINUE READING

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Key Quantitative Results

  • Results of adopting learning for the task are encouraging, scoring a +15% improvement in F1 measure over a nonlearning-based clustering baseline.

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