SentiVeillance SDK

Face identification and movement tracking for video surveillance systems

SentiVeillance SDK is designed for developing software that performs biometric face identification and detects moving pedestrians or vehicles or other objects using live video streams from high-resolution digital surveillance cameras.

The SDK is used for passive identification – when passers-by do not make any efforts to be recognized. List of possible uses includes law enforcement, security, attendance control, visitor counting, traffic monitoring and other commercial applications.

Available as a software development kit that allows solution development for Microsoft Windows and Linux platforms.

Download Brochure (PDF).

Download demo application.

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System Requirements and Supported Cameras

  • PC or server with x86-64 (64-bit) compatible processor:
    • 3 GHz or better processor with 4 processor cores is recommended for systems with 1 or 2 cameras connected to the same PC or server. Systems with more cameras will need a graphical processing unit (see below).
    • SSE2 support is required. Processors that do not support SSE2 cannot run the SentiVeillance algorithm. Please check if a particular processor model supports SSE2 instruction set.
    • At least 2 processor cores are required to process surveillance data from one camera with several faces in a frame. If there are more than 2 cameras in a surveillance system, several networked PCs or a multi-processor server will be required to process data from the cameras.
    • If large number of faces in a frame is expected, more processor cores, more powerful processor or even multi-processor server may be required to process surveillance data and keep the acceptable performance.
  • A graphical processing unit (GPU) is needed for surveillance system with more than 2 cameras connected to the same PC or server.
    • NVIDIA GeForce GTX 1080 GPU or better is recommended for systems with up to 10 cameras.
    • 1 GB of vRAM is recommended for any amount of cameras.
      2 GB of vRAM is recommended if monitor is used.
    • Compute Capability 3.5 or better should be supported by the GPU.
    • CUDA 8.0 toolkit or newer is required
    • cuDNN 7 library is required.
  • At least 8 GB of RAM.
  • A high-resolution digital camera. The camera resolution may vary depending on the actual application. The recommended resolution is about 2 MegaPixel, as processing video from cameras with higher resolution will require more free RAM and more powerful processor to keep the acceptable frame rate.
    These supported cameras are suitable for using with SentiVeillance 6.0 SDK:
    • Any IP camera, that supports RTSP (Real Time Streaming Protocol):
      • Only RTP over UDP is supported.
      • VLC framework can be optionally used for reading video streams.
      • H.264/MPEG-4 AVC or Motion JPEG should be used for encoding the video stream.
    • These specific high-resolution cameras are also supported:
      • Axis M1114 camera (Microsoft Windows and Linux)
      • Basler BIP2-1600-25c-DN IP camera (Microsoft Windows and Linux)
      • Cisco 4500 IP camera (Microsoft Windows only)
      • Mobotix S14D and Mobotix DualNight M12 IP cameras (Microsoft Windows and Linux)
      • PiXORD N606 camera (Microsoft Windows and Linux)
      • Prosilica GigE Vision camera (Microsoft Windows and Linux)
      • Sony SNC-CS50 camera (Microsoft Windows and Linux)
    • Any high-resolution digital camera that is accessible using:
      • DirectShow interface for Microsoft Windows platform;
      • GStreamer interface for Linux platform.
    • Any other device support can be added by customers using the provided Device Manager Plug-in Framework. Please refer to the SentiVeillance 6.0 SDK documentation for the detailed information.
  • Microsoft Windows specific:
    • Microsoft Windows Vista / 7 / 8 / 10 / Server 2008 / Server 2008 R2 / Server 2012, 64-bit.
    • Microsoft .NET framework 3.5 or newer (for .NET components usage).
    • Microsoft DirectX 9.0 or later.
    • One of following development environments for application development:
      • Microsoft Visual Studio 2012 or newer (for application development under C/C++, C#, Visual Basic .Net)
      • Sun Java 1.6 SDK or later
  • Linux specific:
    • Ubuntu 16.04 OS
    • glibc 2.11.3 or newer
    • GStreamer 1.2.2 or newer with gst-vaapi plugins installed for hardware accelerated video decoding
    • libgudev-1.0 164-3 or newer
    • wxWidgets 3.0.0 or newer libs and dev packages (to build and run SDK samples and applications based on them)
    • Sun Java 1.6 SDK or later (for application development with Java)