GSoC’20 RoboComp project: Human recognition (identification) using multi-modal perception system

18th July 2020

Multiple human tracking is the process of locating multiple persons over a sequence of frames (video). The MHT problem can be viewed as a data association problem where the goal is to associate detections across frames in a video sequence.

MHT can be divided into 3 steps:

• Detection: In each frame of the video we need to find the bounding box for each person present

• Multiple Object Tracking: Multiple Object Tracking is the problem of automatically identifying multiple objects in a video and representing them as a set of trajectories with high accuracy.

• Person re-identification(ReID): Reid is associating images of the same person taken from different cameras or from the same camera at different points in time. Usually, re-identification is constrained to a small time period and a small area covered by cameras

Technologies

a) CenterTrack presents a simultaneous detection and tracking algorithm that is simple, faste, and accurate. Their tracker, applies a detection model to a pair of images and detections from the prior frame to localizes objects and predicts their associations.

b) Torch-reid Torchreid is a library for deep-learning person re-identification, written in PyTorch.

Back To The Top

References

• CenterTrack

  Tracking Objects as Points,
  Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl,
  arXiv technical report (arXiv 2004.01177)

• Torchreid

  Tracking Objects as Points,
  Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl,
  arXiv technical report (arXiv 2004.01177)
  — Shubh Maheshwari