MXSERVER: Forensic Media Analysis Incorporating Face Recognition


  1. A Datasheet on MXSERVER

  2. A Whitepaper on Countering the Terrorist Threat Using Face Recognition

  3. Watch some Videos on MXSERVER 

  4. MXSERVER Clients

  5. More Detail on MXSERVER

 

MXSERVER, from Tygart Technology,  is a Big Data cloud-enabled and virtualised video and photographic analysis solution incorporating face recognition.

  • It can be run and maintained in most virtualised environments and can be hosted in a public cloud, private cloud or installed on local servers.
  • It is completely browser-based, allowing multi-user role-based authentication with multiple public or private watchlists.
  • It has a complete set of programming interfaces to allow integration into other systems and workflows allowing it to be run as a “black-box” engine.
  • Using MXSERVER, all faces from the ingested video or photographs are:
    • Extracted and cropped.
    • Searched against a watchlist.
      (Matches resulting in watchlist hits which can be pushed to external systems)
    • Indexed so the media can be searched with a photograph.
      (where have we seen this person before?)
  • Media inputs to MXSERVER may include:
    • Live surveillance cameras (CCTV).
    • Body Worn Video.
    • Archived video.
    • Online Sources (YouTube, Facebook etc).
    • Confiscated hardrives, phones, PCs (Digital Forensics).
    • Live from police mobile phones.
    • Members of the public.
  • MXSERVER is linearly scalable, simply by adding / removing “worker” virtual machines.
  • Allevate also offers a low-bandwidth live surveillance option that moves some processing next to the camera to:
    • Perform face detection, pose correction, best face selection.
    • Create JPGs of individually cropped faces.
      Therefore, only JPG images of faces seen in the video stream are sent over the network to MXSERVER.
    • http://allevate.com/index.php/facesearcher/
  • MXSERVER is independent of the face recognition algorithm and is already integrated with face recognition algorithms of multiple vendors.