Features for Multi-target Multi-camera Tracking and Re-identification

@article{Ristani2018FeaturesFM,
  title={Features for Multi-target Multi-camera Tracking and Re-identification},
  author={Ergys Ristani and Carlo Tomasi},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={6036-6046}
}
Multi-Target Multi-Camera Tracking (MTMCT) tracks many people through video taken from several cameras. Person Re-Identification (Re-ID) retrieves from a gallery images of people similar to a person query image. We learn good features for both MTMCT and Re-ID with a convolutional neural network. Our contributions include an adaptive weighted triplet loss for training and a new technique for hard-identity mining. Our method outperforms the state of the art both on the DukeMTMC benchmarks for… CONTINUE READING

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