What’s New in FindFace CIBR 2.1.1

New Features:

  • Upload a photo to a case: the end user is now able to upload only photos, videos, or photos along with videos to a case.

  • Rematching clusters with the record index: once new photos are uploaded to the record index, the system checks them against all existing clusters of open cases to find out new matches.

  • “Inbox” of cases: the system marks cases that have at least one unacknowledged case cluster with a special sign so that the end user does not miss it.

    See Case Files

Technical Changes:

  • Technical architecture: microservices instead of monolith.

    See Architecture

  • Docker-based distribution: FindFace CIBR 2.1.1 runs as a set of docker containers described in a docker-compose file.

  • Deployment: FindFace CIBR is distributed with its own installer now.

  • CentOS / Debian support.

Enhanced Algorithms, UI, UX:

  • Improvements to the mechanism of clustering and more flexible work with clusters: clusters can now be manually merged and unmerged.

  • Record index batch upload reinstated.

  • Enhanced Daily search functionality: last 24-hour’ location registration of the objects of interest in remote monitoring.

Fresh Neural Networks:

  • Face detection: a new face detection model face.jasmine_fast.003 with improved characteristics.

  • Face image normalization: new face image normalization models facenorm.multicrop_full_center_size400 and facenorm.multicrop_full_crop2x_size400 that use smarter normalization algorithm and a new version bee.v3 with improved characteristics.

  • Face recognition: brand-new nectarine_xs_320 and nectarine_m_160 face recognition models, much faster and more accurate than preceding models.

  • Face quality recognition: a new version quality_fast.v1 that predicts face quality to get the best shot and filter trash.