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Person Re-Identification in Different Cameras
- Project
- 15026 PS-CRIMSON
- Type
- New standard
- Description
- State-of-the-art accuracy in person re-identification
- Real-time
- Robust to changes in person gait, appearance, pose, illumination and camera orientation
- The trained neural network only minorly reduces its re-identification accuracy when applied on the multi-camera setups different from the training multi-camera setup
- Contact
- Egor Bondarev
- e.bondarev@tue.nl
- Technical features
Input(s):
- Timestamped video streams from multiple cameras
- Bounding boxes of detected pedestrians
- UUID of each detected pedestrians
Main feature(s):
- The component is able to detect a person and find his/her previous appearances in the recordings from other cameras in a multi-camera network
Output(s):
- For each queried pedestrian: all previous detections in different cameras, i.e. UUID of each previous detection
- Timestamped moving trajectory of a pedestrian
- Integration constraints
- Accurate timestamping of the captured video is required
- SW constraints: no
- HW constraints: NVIDIA GPU, 8 GB GPU RAM
- Targeted customer(s)
ViNotion, Police, surveillance and security operators, Research community (via open source).
- Conditions for reuse
Licensing
- Confidentiality
- Public
- Publication date
- 13-01-2020
- Involved partners
- Eindhoven University of Technology (NLD)