On Detection, Data Association and Segmentation for Multi-Target Tracking

@article{Tian2019OnDD,
  title={On Detection, Data Association and Segmentation for Multi-Target Tracking},
  author={Yicong Tian and Afshin Dehghan and Mubarak Shah},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2019},
  volume={41},
  pages={2146-2160}
}
In this work, we propose a tracker that differs from most existing multi-target trackers in two major ways. [] Key Method The proposed algorithm consists of two main components: structured learning and Lagrange dual decomposition. Our structured learning based tracker learns a model for each target and infers the best locations of all targets simultaneously in a video clip. The inference of our structured learning is achieved through a new Target Identity-aware Network Flow (TINF), where each node in the…

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