SentiVeillance SDK

Persons or vehicles recognition and tracking for video surveillance systems

SentiVeillance SDK is designed for developing software that performs biometric face identification, detects moving pedestrians or vehicles or other objects and performs automatic license plate recognition using live video streams from 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.

Download 30-day SDK Trial.

System Requirements and Supported Cameras

The requirements below are provided for a single computational node (PC or server) used to run the SentiVeillance algorithms. Multiple nodes can be connected together via network to support larger surveillance systems.

  • PC or server with x86-64 (64-bit) compatible processor:
    • 3 GHz or better processor with 6 cores is recommended.
    • AVX2 support is highly recommended. Processors that do not support AVX2 will still run the SentiVeillance algorithms, but in a mode, which will not provide the specified performance. Most modern processors support this instruction set, but please check if a particular processor model supports it.
  • Graphical processing unit (GPU):
    • a GPU is required if a SentiVeillance component with any of the supported modalities is run to process more than 2 video streams simultaneously.
    • NVIDIA GeForce GTX 1080 GPU or better is recommended to process up to 10 video streams on a node.
    • Several GPUs can be used on the same machine to process larger number of video streams.
    • at least 6 GB of VRAM is recommended.
    • Compute Capability 3.5 or better should be supported by the GPU.
    • CUDA 10.1 toolkit or newer is required
    • cuDNN 7.5 library is required.
  • At least 8 GB of RAM.
  • High-resolution digital camera(s). 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 7.2 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.
    • Any high-resolution digital camera that is accessible using:
      • DirectShow or Windows Media or Media Foundation interfaces 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 7.2 SDK documentation for the detailed information.
  • Microsoft Windows specific:
    • Microsoft Windows 7 / 8 / 10 / Server 2008 / Server 2008 R2 / Server 2012, 64-bit.
    • Microsoft .NET framework 4.5 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 1.8 SDK or later
  • Linux specific:
    • Ubuntu 16.04 OS
    • glibc 2.17 or newer
    • GStreamer 1.10.x or newer with gst-vaapi plugins installed for hardware accelerated video decoding
    • libgudev-1.0 219 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 1.8 SDK or later (for application development with Java)
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