Name:
Error Resilient Recurring Gallery Building
Description:
Correctly re-identify people in different images
Professor — Lab:
Touradj EbrahimiMultimedia Signal Processing Group
Contact:
Evgeniy Upenik

Technical description:
In person re-identification, people must to be correctly identified in images that come from different cameras or are captured at different points in time. In the open-set case, the above needs be achieved for persons that have not been previously observed. We propose a universal method for building a multi-shot gallery of observed reference identities recurrently online.
Papers:
Project status:
inactive — entered showcase: 2021-11-04 — entry updated: 2024-03-15

Source code:
Lab GitHub - last commit: 2021-02-03
Code quality:
This project has not yet been evaluated by the C4DT Factory team. We will be happy to evaluate it upon request.
Project type:
Application
Programming language:
Python
License:
GPL-3.0