Learning to Track: Online Multi-object Tracking by Decision Making

@article{Xiang2015LearningTT,
  title={Learning to Track: Online Multi-object Tracking by Decision Making},
  author={Yu Xiang and Alexandre Alahi and Silvio Savarese},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={4705-4713}
}
Online Multi-Object Tracking (MOT) has wide applications in time-critical video analysis scenarios, such as robot navigation and autonomous driving. In tracking-by-detection, a major challenge of online MOT is how to robustly associate noisy object detections on a new video frame with previously tracked objects. In this work, we formulate the online MOT problem as decision making in Markov Decision Processes (MDPs), where the lifetime of an object is modeled with a MDP. Learning a similarity… CONTINUE READING
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